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JUNE 2015

CONTENT GAZETTEIEEE SIGNAL PROCESSING SOCIETY

[ISSN 2167-5023]


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ASRU 2015IEEE Automatic Speech Recognition and Understanding Workshop

December 13-17, 2015 Scottsdale, Arizona, USA

http://asru2015.org
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www.signalprocessingsociety.org [1] JUNE 2015

APRIL 15, 2015 VOLUME 63 NUMBER 8 ITPRED (ISSN 1053-587X)

REGULAR PAPERS

A Novel Closed-Form Estimator for 3D TMA Using Heterogeneous Sensors http://dx.doi.org/10.1109/TSP.2015.2394405. . . . . . . . . . . .. . . . . . . .

.. ... ... ... ... ... ... ... .. ... .. ... ... ... ... ... ... ... ... ... ... .. ... ... ... . L. Badriasl, T. Sathyan, S. Arulampalam, and A. Finn 1895

http://dx.doi.org/10.1109/TSP.2015.2403268 . . . . . . . . . . . .. . . . . .

.. ... ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... .. C. Meillier, F. Chatelain, O. Michel, and H. Ayasso 1911

Joint Ranging and Synchronization for an Anchorless Network of Mobile Nodes http://dx.doi.org/10.1109/TSP.2015.2391076 . . . . . . . . . . . . . ..

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. T. Rajan and A.-J. van der Veen 1925

Recursive Total Least-Squares Algorithm Based on Inverse Power Method and Dichotomous Coordinate-Descent

Iterations http://dx.doi.org/10.1109/TSP.2015.2405492 . . . . . . . . . . . .. . . . . . . . . ....................... R. Arablouei, K. Do ganay, and S. Werner 1941

Spectrum Sensing Under RF Non-Linearities: Performance Analysis and DSP-Enhanced Receivers

http://dx.doi.org/10.1109/TSP.2015.2401532 . . . . . . . . . . . .. . . . .. .. .. .. . .. .. . E. Rebeiz, A. Shahed Hagh Ghadam, M. Valkama, and D. Cabric 1950

Robust Transmit Code and Receive Filter Design for Extended Targets in Clutter http://dx.doi.org/10.1109/TSP.2015.2404301. . . . . . . . . . . . . ..

.. ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... ... ... ... ... ... ... ... .. S. M. Karbasi, A. Aubry, A. De Maio, and M. H. Bastani 1965

IEEE TRANSACTIONS ONSIGNALPROCESSING (ISSN 1053-587X) is published semimonthly by the Institute of Electrical and Electronics Engineers, Inc. Responsibility for the contents

rests upon the authors and not upon the IEEE, the Society/Council, or its members. 3 Park Avenue, 17th Floor, New York, NY 10016-5997. IEEE Oper-

445 Hoes Lane, Piscataway, NJ 08854-4141. +1 732 981 0060.

only), nonmembers $602.50 per copy. (Note: Postage and handling charge not included.) Member and nonmember subscription prices available upon request. Copyright and Reprint

Abstracting is permitted with credit to the source. Libraries are permitted to photocopy for private use of patrons, provided the per-copy fee of $31.00 is paid through the

CopyrightClearance Center,222 Rosewood Drive, Danvers, MA 01923. Forall othercopying, reprint, or republication permission, writeto Copyrights and Permissions Department, IEEE

Publications Administration, 445 Hoes Lane, Piscataway, NJ 08854-4141. Copyright 2015 by the Institute of Electrical and Electronics Engineers, Inc. All rights reserved. Periodicals

Send address changes to IEEE TRANSACTIONS ONSIGNALPROCESSING, IEEE, 445 Hoes Lane, Piscataway,

NJ 08854-4141. GST Registration No. 125634188. CPC Sales Agreement #40013087. Return undeliverable Canada addresses to: Pitney Bowes IMEX, P.O. Box 4332, Stanton Rd.,

Toronto, ON M5W 3J4, Canada. IEEE prohibits discrimination, harassment and bullying. For more information visit http://www.ieee.org/nondiscrimination.Printed in U.S.A.

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http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TSP.2015.2394405http://dx.doi.org/10.1109/TSP.2015.2403268http://dx.doi.org/10.1109/TSP.2015.2391076http://dx.doi.org/10.1109/TSP.2015.2405492http://dx.doi.org/10.1109/TSP.2015.2401532http://dx.doi.org/10.1109/TSP.2015.2404301http://www.ieee.org/nondiscriminationhttp://www.signalprocessingsociety.org/http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TSP.2015.2394405http://dx.doi.org/10.1109/TSP.2015.2403268http://dx.doi.org/10.1109/TSP.2015.2391076http://dx.doi.org/10.1109/TSP.2015.2405492http://dx.doi.org/10.1109/TSP.2015.2401532http://dx.doi.org/10.1109/TSP.2015.2404301http://www.ieee.org/nondiscriminationhttp://www.signalprocessingsociety.org/


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http://dx.doi.org/10.1109/TSP.2015.2405501 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. S. Zhang, F. Gao, J. Li, and M. Sheng 1977

Generalized Selection Combining for Cognitive Relay Networks Over Nakagami- Fading http://dx.doi.org/10.1109/TSP.2015.2405497 . .

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Y. Deng, L. Wang, M. Elkashlan, K. J. Kim, and T. Q. Duong 1993A Multiple-Detection Probability Hypothesis Density Filter http://dx.doi.org/10.1109/TSP.2015.2407322 . . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . .

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. X. Tang, X. Chen, M. McDonald, R. Mahler, R. Tharmarasa, and T. Kirubarajan 2007

http://dx.doi.org/10.1109/TSP.2015.2407311 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . ................................ J. Ziniel, P. Schniter, and P. Sederberg 2020

http://dx.doi.org/10.1109/TSP.2015.2407324 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . ... .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . M. Kitsunezuka and K. S. J. Pister 2033

MIMO Radar Transmit Beampattern Matching Design http://dx.doi.org/10.1109/TSP.2015.2398841 . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . .

.. ... ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... ... .. X. Zhang, Z. He, L. Rayman-Bacchus, and J. Yan 2049

Optimal Resource Allocation for Detection of a Gaussian Process Using a MAC in WSNs http://dx.doi.org/10.1109/TSP.2015.2407323 . . . .

................................................................................... J. G. Maya, L. Rey Vega, and C. G. Galarza 2057

http://dx.doi.org/10.1109/TSP.2015.2407319 . . . . . . . . . . . . .. . . . . .

.................................................................................... A. Harms, W. U. Bajwa, and R. Calderbank 2070

Compressive Imaging via Approximate Message Passing With Image Denoising http://dx.doi.org/10.1109/TSP.2015.2408558 . . . . . . . . . . . . . ..

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Tan, Y. Ma, and D. Baron 2085

http://dx.doi.org/10.1109/TSP.2015.2395992. . . . . . . . . . . . . .. . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Hellings and W. Utschick 2093

Causal Recursive Parameter Estimation for Discrete-Time Hidden Bivariate Markov Chains http://dx.doi.org/10.1109/TSP.2015.2408557 . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Y. Ephraim and B. L. Mark 2108

Robust Consensus in the Presence of Impulsive Channel Noise http://dx.doi.org/10.1109/TSP.2015.2408564 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . .

.. ... ... ... ... ... ... ... ... ... ... ... ... ... .. ... .. ... ... ... S. Dasarathan, C. Tepedelenlioglu, M. K. Banavar, and A. Spanias 2118

Near Optimal Compressed Sensing Without Priors: Parametric SURE Approximate Message Passing

http://dx.doi.org/10.1109/TSP.2015.2408569 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . .... .. ... ... ... ... ... ... ... ... ... ... .. C. Guo and M. E. Davies 2130

Estimating Periodicities in Symbolic Sequences Using Sparse Modeling http://dx.doi.org/10.1109/TSP.2015.2404314. . . . . . . . . . . . . . .. . . . . . . . . .

................................................................... S. I. Adalbjrnsson, J. Swrd, J. Wallin, and A. Jakobsson 2142

http://dx.doi.org/10.1109/TSP.2015.2408559. . . . . . . . . . . ............. C. U. S. Edussooriya, D. G. Dansereau, L. T. Bruton, and P. Agathoklis 2151

http://dx.doi.org/10.1109/TSP.2015.2416036 . . . . . . . . . . . . .. . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . 2164Information for Authors http://dx.doi.org/10.1109/TSP.2015.2416037 . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . 2165
http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TSP.2015.2405501http://dx.doi.org/10.1109/TSP.2015.2405497http://dx.doi.org/10.1109/TSP.2015.2407322http://dx.doi.org/10.1109/TSP.2015.2407311http://dx.doi.org/10.1109/TSP.2015.2407324http://dx.doi.org/10.1109/TSP.2015.2398841http://dx.doi.org/10.1109/TSP.2015.2407323http://dx.doi.org/10.1109/TSP.2015.2407319http://dx.doi.org/10.1109/TSP.2015.2408558http://dx.doi.org/10.1109/TSP.2015.2395992http://dx.doi.org/10.1109/TSP.2015.2408557http://dx.doi.org/10.1109/TSP.2015.2408564http://dx.doi.org/10.1109/TSP.2015.2408569http://dx.doi.org/10.1109/TSP.2015.2404314http://dx.doi.org/10.1109/TSP.2015.2408559http://dx.doi.org/10.1109/TSP.2015.2416036http://dx.doi.org/10.1109/TSP.2015.2416037http://dx.doi.org/10.1109/TSP.2015.2405501http://dx.doi.org/10.1109/TSP.2015.2405497http://dx.doi.org/10.1109/TSP.2015.2407322http://dx.doi.org/10.1109/TSP.2015.2407311http://dx.doi.org/10.1109/TSP.2015.2407324http://dx.doi.org/10.1109/TSP.2015.2398841http://dx.doi.org/10.1109/TSP.2015.2407323http://dx.doi.org/10.1109/TSP.2015.2407319http://dx.doi.org/10.1109/TSP.2015.2408558http://dx.doi.org/10.1109/TSP.2015.2395992http://dx.doi.org/10.1109/TSP.2015.2408557http://dx.doi.org/10.1109/TSP.2015.2408564http://dx.doi.org/10.1109/TSP.2015.2408569http://dx.doi.org/10.1109/TSP.2015.2404314http://dx.doi.org/10.1109/TSP.2015.2408559http://dx.doi.org/10.1109/TSP.2015.2416036http://dx.doi.org/10.1109/TSP.2015.2416037http://www.signalprocessingsociety.org/


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MAY 1, 2015 VOLUME 63 NUMBER 9 ITPRED (ISSN 1053-587X)

REGULAR PAPER

Clutter Subspace Estimation in Low Rank Heterogeneous Noise Context http://dx.doi.org/10.1109/TSP.2015.2403284 . . . . . . . . . . . . . .. . . . . . . . . .

.. ... ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... ... .. A. Breloy, G. Ginolhac, F. Pascal, and P. Forster 2173

Low-Complexity Multiclass Encryption by Compressed Sensing http://dx.doi.org/10.1109/TSP.2015.2407315 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . .

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. V. Cambareri, M. Mangia, F. Pareschi, R. Rovatti, and G. Setti 2183

A Class of Multivariate Denoising Algorithms Based on Synchrosqueezing http://dx.doi.org/10.1109/TSP.2015.2404307 . . . . . . . . . . . . .. . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Ahrabian and D. P. Mandic 2196

Multiple Change-Points Estimation in Linear Regression Models via Sparse Group Lasso http://dx.doi.org/10.1109/TSP.2015.2411220. . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Zhang, J. Geng, and L. Lai 2209

Distributed Multi-Agent Online Learning Based on Global Feedback http://dx.doi.org/10.1109/TSP.2015.2403288 . . . . . . . . . . . . .. . . . . . . . . . . . . ..

.. ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... . J. Xu, C. Tekin, S. Zhang, and M. van der Schaar 2225

IEEE TRANSACTIONS ONSIGNALPROCESSING (ISSN 1053-587X) is published semimonthly by the Institute of Electrical and Electronics Engineers, Inc. Responsibility for the contents

rests upon the authors and not upon the IEEE, the Society/Council, or its members. 3 Park Avenue, 17th Floor, New York, NY 10016-5997.IEEE Operations

445 Hoes Lane, Piscataway, NJ 08854-4141. +1 732 981 0060.

members $602.50 percopy. (Note: Postage and handling charge not included.) Member and nonmember subscription prices available upon request.

Abstracting is permitted with credit to the source. Libraries are permitted to photocopy for private use of patrons, provided the per-copy fee of $31.00 is paid through the Copyright Clear-

ance Center, 222 Rosewood Drive, Danvers, MA 01923. For all other copying, reprint, or republication permission, write to Copyrights and Permissions Department, IEEE Publications

Administration, 445 Hoes Lane, Piscataway, NJ 08854-4141. Copyright 2015 by the Institute of Electrical and Electronics Engineers, Inc. All rights reserved. Send ad-

dress changes to IEEE TRANSACTIONS ONSIGNALPROCESSING, IEEE, 445 Hoes Lane, Piscataway, NJ 08854-4141. GST Registration No. 125634188. CPC Sales Agreement #40013087.

Return undeliverable Canada addresses to: Pitney Bowes IMEX, P.O. Box 4332, Stanton Rd., Toronto, ON M5W 3J4, Canada. IEEE prohibits discrimination, harassment and bullying.

For more information visit http://www.ieee.org/nondiscrimination.Printed in U.S.A.

_________________________
http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TSP.2015.2403284http://dx.doi.org/10.1109/TSP.2015.2407315http://dx.doi.org/10.1109/TSP.2015.2404307http://dx.doi.org/10.1109/TSP.2015.2411220http://dx.doi.org/10.1109/TSP.2015.2403288http://www.ieee.org/nondiscriminationhttp://www.signalprocessingsociety.org/http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TSP.2015.2403284http://dx.doi.org/10.1109/TSP.2015.2407315http://dx.doi.org/10.1109/TSP.2015.2404307http://dx.doi.org/10.1109/TSP.2015.2411220http://dx.doi.org/10.1109/TSP.2015.2403288http://www.ieee.org/nondiscriminationhttp://www.signalprocessingsociety.org/


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Constructive Multiuser Interference in Symbol Level Precoding for the MISO Downlink Channel

http://dx.doi.org/10.1109/TSP.2015.2404302 . . . . . . . . . . . .. . . . . . . . . . . . . .. ........................... M. Alodeh, S. Chatzinotas, and B. Ottersten 2239

Super-Resolution on the Sphere Using Convex Optimization http://dx.doi.org/10.1109/TSP.2015.2399861 . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T. Bendory, S. Dekel, and A. Feuer 2253

http://dx.doi.org/10.1109/TSP.2015.2411222 . . . . . . . . . . . . . .. . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. D. Richmond and L. L. Horowitz 2263

Bounded Component Analysis of Noisy Underdetermined and Overdetermined Mixtures http://dx.doi.org/10.1109/TSP.2015.2404312. . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Cruces 2279

Robust Precoder Design for MIMO Relay Networks Over Double Correlated Rician Channels http://dx.doi.org/10.1109/TSP.2015.2408561 . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Z. Luo, S.-H. Leung, and X. Yu 2295

Blind Separation of Quasi-Stationary Sources: Exploiting Convex Geometry in Covariance Domain

http://dx.doi.org/10.1109/TSP.2015.2404577 . . . . . . . . . . . .. . . . . . . . . . ... .. .. .. .. .. .. .. .. .. .. X. Fu, W.-K. Ma, K. Huang, and N. D. Sidiropoulos 2306

Adaptive Search and Tracking of Sparse Dynamic Targets Under Resource Constraints http://dx.doi.org/10.1109/TSP.2015.2405493. . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G. Newstadt, D. Wei, and A. O. Hero 2321

Deterministic Sensor Selection for Centralized State Estimation Under Limited Communication Resource

http://dx.doi.org/10.1109/TSP.2015.2412916 . . . . . . . . . . . .. . . . . . . . . . ... .. .. .. .. .. .. .. .. .. .. . C. Yang, J. Wu, X. Ren, W. Yang, H. Shi, and L. Shi 2336

Multi-Sensor-Based Aperiodic Least-Squares Estimation for Networked Systems With Transmission Constraints

http://dx.doi.org/10.1109/TSP.2015.2413385 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . ... .. .. .. .. .. .. .. .. .. .. .. .. .. .. H. Song, W.-A. Zhang, L. Yu, and L. Shi 2349

Adaptive KPCA Modeling of Nonlinear Systems http://dx.doi.org/10.1109/TSP.2015.2412913 . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . .

.. ... ... ... ... ... ... ... .. ... .. ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... .. Z. Li, U. Kruger, L. Xie, A. Almansoori, and H. Su 2364

Measure of Nonlinearity for Estimation http://dx.doi.org/10.1109/TSP.2015.2405495 . . . . . . . . . . . . .. . . . . . .... ... ... ... ... ... .. Y. Liu and X. R. Li 2377

http://dx.doi.org/10.1109/TSP.2015.2405503 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . .................................... S. Ravishankar and Y. Bresler 2389

Azimuth and Elevation Estimation With Rotating Long-Baseline Interferometers http://dx.doi.org/10.1109/TSP.2015.2405506 . . . . . . . . . . . . . ..

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Z.-M. Liu and F.-C. Guo 2405

Sensor Network Localization by Augmented Dual Embedding http://dx.doi.org/10.1109/TSP.2015.2411211. . . . . S. Gepshtein and Y. Keller 2420

Local-Set-Based Graph Signal Reconstruction http://dx.doi.org/10.1109/TSP.2015.2411217. . . . . . . . . . . ............. X. Wang, P. Liu, and Y. Gu 2432
http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TSP.2015.2404302http://dx.doi.org/10.1109/TSP.2015.2399861http://dx.doi.org/10.1109/TSP.2015.2411222http://dx.doi.org/10.1109/TSP.2015.2404312http://dx.doi.org/10.1109/TSP.2015.2408561http://dx.doi.org/10.1109/TSP.2015.2404577http://dx.doi.org/10.1109/TSP.2015.2405493http://dx.doi.org/10.1109/TSP.2015.2412916http://dx.doi.org/10.1109/TSP.2015.2413385http://dx.doi.org/10.1109/TSP.2015.2412913http://dx.doi.org/10.1109/TSP.2015.2405495http://dx.doi.org/10.1109/TSP.2015.2405503http://dx.doi.org/10.1109/TSP.2015.2405506http://dx.doi.org/10.1109/TSP.2015.2411211http://dx.doi.org/10.1109/TSP.2015.2411217http://dx.doi.org/10.1109/TSP.2015.2404302http://dx.doi.org/10.1109/TSP.2015.2399861http://dx.doi.org/10.1109/TSP.2015.2411222http://dx.doi.org/10.1109/TSP.2015.2404312http://dx.doi.org/10.1109/TSP.2015.2408561http://dx.doi.org/10.1109/TSP.2015.2404577http://dx.doi.org/10.1109/TSP.2015.2405493http://dx.doi.org/10.1109/TSP.2015.2412916http://dx.doi.org/10.1109/TSP.2015.2413385http://dx.doi.org/10.1109/TSP.2015.2412913http://dx.doi.org/10.1109/TSP.2015.2405495http://dx.doi.org/10.1109/TSP.2015.2405503http://dx.doi.org/10.1109/TSP.2015.2405506http://dx.doi.org/10.1109/TSP.2015.2411211http://dx.doi.org/10.1109/TSP.2015.2411217http://www.signalprocessingsociety.org/


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Adaptation, Detection, Estimation, and Learning

Distributed detection and estimation Distributed adaptation over networks Distributed learning over networks Distributed target tracking Bayesian learning; Bayesian signal processing Sequential learning over networks Decision making over networks

Distributed dictionary learning

Distributed game theoretic strategies Distributed information processing Graphical and kernel methods Consensus over network systems Optimization over network systems

Communications, Networking, and Sensing

Distributed monitoring and sensing Signal processing for distributed communications and

networking

Signal processing for cooperative networking

Signal processing for network security

Optimal network signal processing and resourceallocation

Modeling and Analysis

Performance and bounds of methods Robustness and vulnerability Network modeling and identification

Modeling and Analysis (cont.)

Simulations of networked information processingsystems

Social learning Bio-inspired network signal processing Epidemics and diffusion in populations

Imaging and Media Applications

Image and video processing over networks

Media cloud computing and communication Multimedia streaming and transport Social media computing and networking Signal processing for cyber-physical systems Wireless/mobile multimedia

Data Analysis

Processing, analysis, and visualization of big data Signal and information processing for crowd

computing

Signal and information processing for the Internet ofThings

Emergence of behaviorEmerging topics and applications

Emerging topics Applications in life sciences, ecology, energy, social

networks, economic networks, finance, social

sciences, smart grids, wireless health, robotics,

transportation, and other areas of science and

engineering

IEEE TRANSACTIONSON

SIGNAL AND INFORMATION PROCESSING OVER

NETWORKS

The new publishes high-quality papers

that extend the classical notions of processing of signals defined over vector spaces (e.g. time and space) to

processing of signals and information (data) defined over networks, potentially dynamically varying. In signal

processing over networks, the topology of the network may define structural relationships in the data, or

may constrain processing of the data. Topics of interest include, but are not limited to the following:

Editor-in-

-ieee

Now accepting paper submissions

_________________________________
http://www.signalprocessingsociety.org/https://mc.manuscriptcentral.com/tsipn-ieeehttps://mc.manuscriptcentral.com/tsipn-ieeehttps://mc.manuscriptcentral.com/tsipn-ieeehttps://mc.manuscriptcentral.com/tsipn-ieeehttp://www.signalprocessingsociety.org/


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NEW PUBLICATION:

Transactions on Signal and Information Processing over Networks (T-SIPN)*

http://www.signalprocessingsociety.org/publications/periodicals/tsipn/

>>We are accepting paper submissions: please submit a manuscript here


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Modeling and Analysis (MA)

o Performance and bounds of methods (MA-PBM)o Robustness and vulnerability (MA-RV)

o Network modeling and identification (MA-NMI)o Simulations of networked information processing systems (MA-SNIPS)o Social learning (MA-SL)o Bio-inspired network signal processing (MA-BNSP)o Epidemics and diffusion in populations (MA-EDP)

Imaging and Media Applications (IMA)

o Image and video processing over networks (IMA-IVPN)

o Media cloud computing and communication (IMA-MCCC)o Multimedia streaming and transport (IMA-MST)

o Social media computing and networking (IMA-SMCN)o Signal processing for cyber-physical systems (IMA-SPCPS)o Wireless/mobile multimedia (IMA-WMM)

Data Analysis (DA)

o Processing, analysis, and visualization of big data (DA-BD)o Signal and information processing for crowd computing (DA-CC)

o Signal and information processing for the Internet of Things (DA-IOT)o Emergence of behavior (DA-EB)

Emerging topics and applications (ETA)

o Emerging topics (ETA-ET)o Applications in life sciences, ecology, energy, social networks, economic networks,

finance, social sciences etc. smart grids, wireless health, robotics, transportation, andother areas of science and engineering (ETA-APP)

>>We are accepting paper submissions: please submit a manuscript here


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MAY 2015 VOLUME 23 NUMBER 5 ITASFA (ISSN 2329-9290)

Inferring Metrical Structure in Music Using Particle Filters http://dx.doi.org/10.1109/TASLP.2015.2409737. . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . ... ... .. ... .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... F. Krebs, A. Holzapfel, A. T. Cemgil, and G. Widmer 817

Underdetermined Convolutive BSS: Bayes Risk Minimization Based on a Mixture of Super-Gaussian PosteriorApproximation http://dx.doi.org/10.1109/TASLP.2015.2409778. . . . . . . . . . . . . .. . . . . . . . . . . . . .. . .. ... ... ... ... ... ... ... ... ... . J. Cho and C. D. Yoo 828

http://dx.doi.org/10.1109/TASLP.2015.2409779. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . H. Mu, W.-S. Gan, and E.-L. Tan 840

Optimal Near-End Speech Intelligibility Improvement Incorporating Additive Noise and Late Reverberation Under anApproximation of the Short-Time SII http://dx.doi.org/10.1109/TASLP.2015.2409780 . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... . R. C. Hendriks, J. B. Crespo, J. Jensen, and C. H. Taal 851

IEEE/ACM TRANSACTIONS ONAUDIO, S PEECH, AND LANGUAGE PROCESSING (ISSN 2329-9290) is published bimonthly in print and monthly online by the Institute of Electrical and

Electronics Engineers, Inc. Responsibility for the contents rests upon the authors and not upon the IEEE, the Society/Council, or its members. 3 Park Avenue,17th Floor, New York, NY 10016-5997. 445 Hoes Lane, Piscataway, NJ 08854-4141. +1 732 981 0060.

onmember subscription

prices available upon request. Abstracting is permitted with credit to the source. Libraries are permitted to photocopy for private use of patrons,

provided the per-copy fee of $31.00 is paid through the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923. For all other copying, reprint, or republication permission,

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http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TASLP.2015.2409737http://dx.doi.org/10.1109/TASLP.2015.2409778http://dx.doi.org/10.1109/TASLP.2015.2409779http://dx.doi.org/10.1109/TASLP.2015.2409780http://www.ieee.org/nondiscriminationhttp://www.signalprocessingsociety.org/http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TASLP.2015.2409737http://dx.doi.org/10.1109/TASLP.2015.2409778http://dx.doi.org/10.1109/TASLP.2015.2409779http://dx.doi.org/10.1109/TASLP.2015.2409780http://www.ieee.org/nondiscriminationhttp://www.signalprocessingsociety.org/


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http://dx.doi.org/10.1109/TASLP.2015.2409785 . . . . . . . . . . . .. . . . . . . . . . . . . .. ............................. A. H. Abdelaziz, S. Zeiler, and D. Kolossa 863

Combined Beamformers for Robust Broadband Regularized Superdirective Beamforming http://dx.doi.org/10.1109/TASLP.2015.2410139. . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. Berkun, I. Cohen, and J. Benesty 877

Evaluation of Statistical Inference Tests Applied to Subjective Audio Quality Data With Small Sample Sizehttp://dx.doi.org/10.1109/TASLP.2015.2412462 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Breebaart 887

Harmonic Bandwidth Companding for Separation of Overlapping Harmonics in Pitched Signalshttp://dx.doi.org/10.1109/TASLP.2015.2412464 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. Zivanovic 898

Laplace Group Sensing for Acoustic Models http://dx.doi.org/10.1109/TASLP.2015.2412466 . . . . . . . . . . . .. . . . . . . . .... ... ... ... ... ... ... J.-T. Chien 909Design of Low Complexity Adjustable Filter Bank for Personalized Hearing Aid Solutions http://dx.doi.org/10.1109/TASLP.2015.2409774 . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Y. Wei and Y. Wang 923

http://dx.doi.org/10.1109/TASLP.2015.2410140 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . ............................ A. Perez-Carrillo and M. M. Wanderley 932Adaptation of Morph-Based Speech Recognition for Foreign Names and Acronyms http://dx.doi.org/10.1109/TASLP.2015.2414818. . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Mansikkaniemi and M. Kurimo 941
http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TASLP.2015.2409785http://dx.doi.org/10.1109/TASLP.2015.2410139http://dx.doi.org/10.1109/TASLP.2015.2412462http://dx.doi.org/10.1109/TASLP.2015.2412464http://dx.doi.org/10.1109/TASLP.2015.2412466http://dx.doi.org/10.1109/TASLP.2015.2409774http://dx.doi.org/10.1109/TASLP.2015.2410140http://dx.doi.org/10.1109/TASLP.2015.2414818http://dx.doi.org/10.1109/TASLP.2015.2409785http://dx.doi.org/10.1109/TASLP.2015.2410139http://dx.doi.org/10.1109/TASLP.2015.2412462http://dx.doi.org/10.1109/TASLP.2015.2412464http://dx.doi.org/10.1109/TASLP.2015.2412466http://dx.doi.org/10.1109/TASLP.2015.2409774http://dx.doi.org/10.1109/TASLP.2015.2410140http://dx.doi.org/10.1109/TASLP.2015.2414818http://www.signalprocessingsociety.org/


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http://www.signalprocessingsociety.org/http://www.signalprocessingsociety.org/


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MAY 2015 VOLUME 24 NUMBER 5 IIPRE4 (ISSN 1057-7149)

PAPERS

http://dx.doi.org/10.1109/TIP.2015.2395961

. . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Lu, N. He, J. Xue, J. Dong, and L. Shao 1449Color Correction Using Root-Polynomial Regression http://dx.doi.org/10.1109/TIP.2015.2405336 . . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . .

... ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... G. D. Finlayson, M. Mackiewicz, and A. Hurlbert 1460Statistical Model of JPEG Noises and Its Application in Quantization Step Estimation http://dx.doi.org/10.1109/TIP.2015.2405477 . . . . . . . . .

... ... .. ... .. ... ... ... ... ... ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... . B. Li, T.-T. Ng, X. Li, S. Tan, and J. Huang 1471Low-Rank Prior in Single Patches for Nonpointwise Impulse Noise Removal http://dx.doi.org/10.1109/TIP.2015.2400225 . . . . . . . . . . . .. . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. Wang, M. Pakleppa, and E. Trucco 1485Cross-Modal Learning to Rank via Latent Joint Representation http://dx.doi.org/10.1109/TIP.2015.2403240 . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . .

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. F. Wu, X. Jiang, X. Li, S. Tang, W. Lu, Z. Zhang, and Y. Zhuang 1497Robust Discriminative Tracking via Landmark-Based Label Propagation http://dx.doi.org/10.1109/TIP.2015.2405479. . . . . . . . . . . . .. . . . . . . . . . . .

... ... .. ... .. ... ... ... ... ... ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... . Y. Wu, M. Pei, M. Yang, J. Yuan, and Y. Jia 1510Depth Superresolution by Transduction http://dx.doi.org/10.1109/TIP.2015.2405342 . . . . . . . . . . . .. ... .. .. .. .. .. .. . B. Ham, D. Min, and K. Sohn 1524Symmetric Smoothing Filters From Global Consistency Constraints http://dx.doi.org/10.1109/TIP.2014.2383316. . . . . . . . . . . . . .. . . . . . . . . . . . .. . .

... ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... .. S. M. Haque, G. P. Pai, and V. M. Govindu 1536Tree Leaves Extraction in Natural Images: Comparative Study of Preprocessing Tools and Segmentation Methods

http://dx.doi.org/10.1109/TIP.2015.2400214 . . . . . . . ........ M. Grand-Brochier, A. Vacavant, G. Cerutti, C. Kurtz, J. Weber, and L. Tougne 1549Estimation of Signal-Dependent Noise Level Function in Transform Domain via a Sparse Recovery Model

http://dx.doi.org/10.1109/TIP.2015.2405417 . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. J. Yang, Z. Gan, Z. Wu, and C. Hou 1561Graph-Based Representation for Multiview Image Geometry http://dx.doi.org/10.1109/TIP.2015.2400817 . . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . .

... ... .. ... .. ... ... ... ... ... ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... T. Maugey, A. Ortega, and P. Frossard 1573On the Convergence of Nonconvex Minimization Methods for Image Recovery http://dx.doi.org/10.1109/TIP.2015.2401430 . . . . . . . . . . . .. . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Xiao, M. K.-P. Ng, and Y.-F. Yang 1587

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http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TIP.2015.2395961http://dx.doi.org/10.1109/TIP.2015.2405336http://dx.doi.org/10.1109/TIP.2015.2405477http://dx.doi.org/10.1109/TIP.2015.2400225http://dx.doi.org/10.1109/TIP.2015.2403240http://dx.doi.org/10.1109/TIP.2015.2405479http://dx.doi.org/10.1109/TIP.2015.2405342http://dx.doi.org/10.1109/TIP.2014.2383316http://dx.doi.org/10.1109/TIP.2015.2400214http://dx.doi.org/10.1109/TIP.2015.2405417http://dx.doi.org/10.1109/TIP.2015.2400817http://dx.doi.org/10.1109/TIP.2015.2401430http://www.signalprocessingsociety.org/http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TIP.2015.2395961http://dx.doi.org/10.1109/TIP.2015.2405336http://dx.doi.org/10.1109/TIP.2015.2405477http://dx.doi.org/10.1109/TIP.2015.2400225http://dx.doi.org/10.1109/TIP.2015.2403240http://dx.doi.org/10.1109/TIP.2015.2405479http://dx.doi.org/10.1109/TIP.2015.2405342http://dx.doi.org/10.1109/TIP.2014.2383316http://dx.doi.org/10.1109/TIP.2015.2400214http://dx.doi.org/10.1109/TIP.2015.2405417http://dx.doi.org/10.1109/TIP.2015.2400817http://dx.doi.org/10.1109/TIP.2015.2401430http://www.signalprocessingsociety.org/


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http://dx.doi.org/10.1109/TIP.2015.2395715 . . . . . . . . . . . . ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. J. Ma, J. Li, P. C. Yuen, and P. Li 1599

http://dx.doi.org/10.1109/TIP.2015.2409568 . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . .. . ... .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . A. Tuysuzoglu, W. C. Karl, I. Stojanovic, D. Castan, and M. S. nl 1614

Surface Reconstruction in Gradient-Field Domain Using Compressed Sensing http://dx.doi.org/10.1109/TIP.2015.2409565 . . . . . . . . . . . .. . . . . ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... M. Rostami, O. V. Michailovich, and Z. Wang 1628

Saliency Region Detection Based on Markov Absorption Probabilities http://dx.doi.org/10.1109/TIP.2015.2403241 . . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Sun, H. Lu, and X. Liu 1639

http://dx.doi.org/10.1109/TIP.2015.2409553. . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... W. Guo, L. Cao, T. X. Han, S. Yan, and C. Xu 1650

Minimum Risk Wavelet Shrinkage Operator for Poisson Image Denoising http://dx.doi.org/10.1109/TIP.2015.2409566 . . . . . . . . . . . . .. . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . W. Cheng and K. Hirakawa 1660

Penrose Demosaicking http://dx.doi.org/10.1109/TIP.2015.2409569 . . . . . . . . . . . . . .. . ................. C. Bai, J. Li, Z. Lin, J. Yu, and Y.-W. Chen 1672Oriented Correlation Models of Distorted Natural Images With Application to Natural Stereopair Quality Evaluation

http://dx.doi.org/10.1109/TIP.2015.2409558 . . . . . . . . . . . .. . . . . . . . . . . . . .. . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . C.-C. Su, L. K. Cormack, and A. C. Bovik 1685
http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TIP.2015.2395715http://dx.doi.org/10.1109/TIP.2015.2409568http://dx.doi.org/10.1109/TIP.2015.2409565http://dx.doi.org/10.1109/TIP.2015.2403241http://dx.doi.org/10.1109/TIP.2015.2409553http://dx.doi.org/10.1109/TIP.2015.2409566http://dx.doi.org/10.1109/TIP.2015.2409569http://dx.doi.org/10.1109/TIP.2015.2409558http://dx.doi.org/10.1109/TIP.2015.2395715http://dx.doi.org/10.1109/TIP.2015.2409568http://dx.doi.org/10.1109/TIP.2015.2409565http://dx.doi.org/10.1109/TIP.2015.2403241http://dx.doi.org/10.1109/TIP.2015.2409553http://dx.doi.org/10.1109/TIP.2015.2409566http://dx.doi.org/10.1109/TIP.2015.2409569http://dx.doi.org/10.1109/TIP.2015.2409558http://www.signalprocessingsociety.org/


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IEEE TRANSACTIONS ON

COMPUTATIONAL IMAGING

The new IEEE Transactions on Computational Imaging seeks original manuscripts for publication. This new

journal will publish research results where computation plays an integral role in the image formation process.

All areas of computational imaging are appropriate, ranging from the principles and theory of computationalimaging, to modeling paradigms for computational imaging, to image formation methods, to the latest innova-

tive computational imaging system designs. Topics of interest include, but are not limited to the following:

Imaging Models andRepresentation

Statistical-model based methods

System and image prior models

Noise models

Graphical and tree-based models

Perceptual models

Computational Sensing

Coded source methods

Structured light

Coded aperture methods

Compressed sensing

Light-field sensing

Plenoptic imaging

Hardware and software systems

Computational Image Creation

Sparsity-based methods

Statistically-based inversion methods,Bayesian regularization

Super-resolution, multi-image fusion

Learning-based methods, Dictionary-based methods

Optimization-based methods; proximaliterative methods, ADMM

Computational Photography

Non-classical image capture, General-ized illumination

Time-of-flight imaging

High dynamic range imaging

Focal stacks

Computational ConsumerImaging

Cell phone imaging

Camera-array systems

Depth cameras

Computational Acoustic Imaging

Multi-static ultrasound imaging

Photo-acoustic imaging

Acoustic tomography

Computational MicroscopicImaging

Holographic microscopy

Quantitative phase imaging

Multi-illumination microscopy

Lensless microscopy

Tomographic Imaging

X-ray CT

PET

SPECT

Magnetic Resonance Imaging

Diffusion tensor imaging

Fast acquisition

Radar Imaging

Synthetic aperture imaging

Inverse synthetic imaging

Terahertz imaging

Geophysical Imaging

Multi-spectral imaging

Ground penetrating radar

Seismic tomography

Multi-spectral Imaging

Multi-spectral imaging

Hyper-spectral imaging

Spectroscopic imaging

Editor-in-Chief: W. Clem Karl, Boston University.To submit a paper go to: https://mc.manuscriptcentral.com/tci-ieee
http://www.signalprocessingsociety.org/https://mc.manuscriptcentral.com/tci-ieeehttps://mc.manuscriptcentral.com/tci-ieeehttp://www.signalprocessingsociety.org/


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The 23rd IEEE International Conference on Image Processing (ICIP) will be held in the PhoenixConvention Centre, Phoenix, Arizona, USA, on September 25 - 28, 2016. ICIP is the worlds largestand most comprehensive technical conference focused on image and video processing and computervision. In addition to the Technical Program, ICIP 2016 will feature an Innovation Program focusedon innovative vision technologies and fostering innovation, entrepreneurship, and networking.The conference will feature world-class speakers, tutorials, exhibits, and a vision technology showcase.

Topics in the ICIP 2016 Technical Program include but are not limited to the following:

Filtering, Transforms, Multi-Resolution ProcessingRestoration, Enhancement, Super-ResolutionComputer Vision Algorithms and TechnologiesCompression, Transmission, Storage, RetrievalComputational ImagingColor and Multispectral ProcessingMulti-View and Stereoscopic ProcessingMulti-Temporal and Spatio-Temporal ProcessingVideo Processing and AnalyticsAuthentication and Biometrics

Biological and Perceptual-based ProcessingVisual Quality AssessmentScanning, Display, and PrintingDocument and Synthetic Visual ProcessingApplications to various fields (e.g., biomedical,Advanced Driving Assist Systems, assistiveliving, security, learning,health and environmental monitoring,manufacturing, consumer electronics)

The ICIP 2016 innovation program will feature a vision technology showcaseof state-of-the-art vision

technologies, innovation challenges, talks by innovation leaders and entrepreneurs, tutorials, andnetworking.

Paper Submission:Prospective authors are invited to submit full-length papers at the conference website,with up to four pages for technical content including figures and references, and with one additionaloptional 5th page for references only. Submission instructions, templates for the required paper format,and information on no show policy are available at www.icip2016.com.

Tutorials and Special Sessions Proposals: Tutorials will be held on September 25, 2016. Tutorialproposals should be submitted to [email protected] and must include title, outline, contactinformation, biography and selected publications for the presenter(s) , and a description of the tutorialand material to be distributed to participants. Special Sessions proposals should be submitted [email protected] and must include a topical title, rationale, session outline, contact

information, and a list of invited papers. For detailed submission guidelines, please refer the ICIP 2016website at www.icip2016.com.

Important Deadlines:Special Session and Tutorial Proposals: November 16, 2015Notification of Special Session and Tutorial Acceptance: December 18, 2015

Paper Submissions: January 25, 2016Notification of Paper Acceptance: April 30, 2016

Visual Technology Innovator Award Nomination: March 30, 2016

Revised Paper Upload Deadline: May 30, 2016Authors Registration Deadline: May 30, 2016

General ChairLina Karam Arizona State University

General Co-ChairAggelos Katsaggelos Northwestern University

Technical Program ChairsFernando Pereira Instituto Superior TcnicoGaurav Sharma University of Rochester

Innovation Program ChairsHaohong Wang TCL Research AmericaJeff Bier BDTI & Embedded Vision Alliance

Finance ChairSohail Dianat Rochester Institute of Technology

Plenary ChairsMichael Marcellin University of ArizonaSethuraman Panchanathan Arizona State University

Special Sessions ChairsDinei Florencio Microsoft Research

Chaker Larabi Poitiers UniversityZhou Wang University of Waterloo

Tutorials ChairsGhassan AlRegib Georgia TechRony Ferzli Intel

Publicity ChairMichel Sarkis Qualcomm Technologies Inc.

Awards ChairsVivek Goyal Boston UniversityIvana Tosic Ricoh Innovations

Exhibits ChairDavid Frakes Arizona State University & Google

Publication ChairsPatrick Le Callet Nantes UniversityBaoxin Li Arizona State University

Local Arrangement ChairsJorge Caviedes IntelPavan Turaga Arizona State University

Registration ChairRicardo De Queiroz

Universidade de BrasiliaConference ManagementConference Management Services

http://www.facebook.com/icip2016https://twitter.com/icip2016/

https://www.linkedin.com/groups/ICIP-2016-6940658

____________________

________________

____________________________________
http://www.signalprocessingsociety.org/http://www.icip2016.com/mailto:[email protected]:[email protected]:[email protected]:[email protected]://www.icip2016.com/http://www.icip2016.com/http://www.facebook.com/icip2016https://twitter.com/icip2016/https://www.linkedin.com/groups/ICIP-2016-6940658mailto:[email protected]:[email protected]://www.linkedin.com/groups/ICIP-2016-6940658mailto:[email protected]:[email protected]://www.icip2016.com/http://www.icip2016.com/http://www.facebook.com/icip2016https://twitter.com/icip2016/https://www.linkedin.com/groups/ICIP-2016-6940658http://www.signalprocessingsociety.org/


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APRIL 2015 VOLUME 10 NUMBER 4 ITIFA6 (ISSN 1556-6013)

EDITORIAL

http://dx.doi.org/10.1109/TIFS.2015.2406111 . . . . . . . . . . . .. . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. Evans, S. Z. Li, S. Marcel, and A. Ross 699

PAPERS

Robust Scheme for Iris Presentation Attack Detection Using Multiscale Binarized Statistical Image Featureshttp://dx.doi.org/10.1109/TIFS.2015.2400393 . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . ... ... .. ... ... ... ... ... ... ... ... .. . R. Raghavendra and C. Busch 703

Attack of Mechanical Replicas: Liveness Detection With Eye Movements http://dx.doi.org/10.1109/TIFS.2015.2405345 . . . . . . . . . . . . . .. . . . . . . ... ... ... ... ... .. ... .. ... ... ... ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... ... O. V. Komogortsev, A. Karpov, and C. D. Holland 716

Pupil Dynamics for Iris Liveness Detection http://dx.doi.org/10.1109/TIFS.2015.2398815 . . . . . . . . . . . . .. . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . A. Czajka 726 http://dx.doi.org/10.1109/TIFS.2015.2398819 . . . . . . . . . . . . . .. . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. F. Smith, A. Wiliem, and B. C. Lovell 736Face Spoof Detection With Image Distortion Analysis http://dx.doi.org/10.1109/TIFS.2015.2400395 . . . .. . . . D. Wen, H. Han, and A. K. Jain 746 http://dx.doi.org/10.1109/TIFS.2015.2406533 . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . .

................................................... S. Tirunagari, N. Poh, D. Windridge, A. Iorliam, N. Suki, and A. T. S. Ho 762 http://dx.doi.org/10.1109/TIFS.2015.2411394 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. C. Garcia, and R. L. de Queiroz 778 http://dx.doi.org/10.1109/TIFS.2015.2400392 . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I. Chingovska and A. R. dos Anjos 787 http://dx.doi.org/10.1109/TIFS.2015.2403306 . . . . . . . . . . . . .. . . . . . . . . . . . . ..

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Yang, Z. Lei, D. Yi, and S. Z. Li 797

_________________________
http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TIFS.2015.2406111http://dx.doi.org/10.1109/TIFS.2015.2400393http://dx.doi.org/10.1109/TIFS.2015.2405345http://dx.doi.org/10.1109/TIFS.2015.2398815http://dx.doi.org/10.1109/TIFS.2015.2398819http://dx.doi.org/10.1109/TIFS.2015.2400395http://dx.doi.org/10.1109/TIFS.2015.2406533http://dx.doi.org/10.1109/TIFS.2015.2411394http://dx.doi.org/10.1109/TIFS.2015.2400392http://dx.doi.org/10.1109/TIFS.2015.2403306http://www.signalprocessingsociety.org/http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TIFS.2015.2406111http://dx.doi.org/10.1109/TIFS.2015.2400393http://dx.doi.org/10.1109/TIFS.2015.2405345http://dx.doi.org/10.1109/TIFS.2015.2398815http://dx.doi.org/10.1109/TIFS.2015.2398819http://dx.doi.org/10.1109/TIFS.2015.2400395http://dx.doi.org/10.1109/TIFS.2015.2406533http://dx.doi.org/10.1109/TIFS.2015.2411394http://dx.doi.org/10.1109/TIFS.2015.2400392http://dx.doi.org/10.1109/TIFS.2015.2403306http://www.signalprocessingsociety.org/


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http://dx.doi.org/10.1109/TIFS.2015.2398812. . . . . . . . . . . ... .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. J. Sanchez, I. Saratxaga, I. Hernez, E. Navas, D. Erro, and T. Raitio 810

http://dx.doi.org/10.1109/TIFS.2015.2407362 . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . ........................................................................ A. Sizov, E. Khoury, T. Kinnunen, Z. Wu, and S. Marcel 821

http://dx.doi.org/10.1109/TIFS.2015.2405412 . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. Hildebrandt and J. Dittmann 833

http://dx.doi.org/10.1109/TIFS.2015.2404294 . . . . . . . . . . . . . .. . . . . . . . . ...................................................................... D. Gragnaniello, G. Poggi, C. Sansone, and L. Verdoliva 849 http://dx.doi.org/10.1109/TIFS.2015.2398817 . . . . . . . . . . . . . .. . . . . . . . . .

.. . .. .. .. . .. .. .. .. . .. .. .. .. . .. . D. Menotti, G. Chiachia, A. Pinto W. R. Schwartz, H. Pedrini, A. X. Falco, and A. Rocha 864

http://dx.doi.org/10.1109/TIFS.2015.2415579. . . . . . . . . . . . . .. . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . 880

Information for Authors http://dx.doi.org/10.1109/TIFS.2015.2415578 . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . 881

ANNOUNCEMENTS

Call for Papers-IEEE Transactions on Computational Imaging http://dx.doi.org/10.1109/TIFS.2015.2415352 . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . 883

Call for Papers-IEEE Transactions on Signal and Information Processing Over Networks http://dx.doi.org/10.1109/TIFS.2015.2415351 . . . . 884
http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TIFS.2015.2398812http://dx.doi.org/10.1109/TIFS.2015.2407362http://dx.doi.org/10.1109/TIFS.2015.2405412http://dx.doi.org/10.1109/TIFS.2015.2404294http://dx.doi.org/10.1109/TIFS.2015.2398817http://dx.doi.org/10.1109/TIFS.2015.2415579http://dx.doi.org/10.1109/TIFS.2015.2415578http://dx.doi.org/10.1109/TIFS.2015.2415352http://dx.doi.org/10.1109/TIFS.2015.2415351http://dx.doi.org/10.1109/TIFS.2015.2398812http://dx.doi.org/10.1109/TIFS.2015.2407362http://dx.doi.org/10.1109/TIFS.2015.2405412http://dx.doi.org/10.1109/TIFS.2015.2404294http://dx.doi.org/10.1109/TIFS.2015.2398817http://dx.doi.org/10.1109/TIFS.2015.2415579http://dx.doi.org/10.1109/TIFS.2015.2415578http://dx.doi.org/10.1109/TIFS.2015.2415352http://dx.doi.org/10.1109/TIFS.2015.2415351http://www.signalprocessingsociety.org/


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The

-

, from November 16, to November

19, 2015. The conference will feature three keynote lectures, up to four tutorials, lectures and poster

:--

.

.

.

:

Rome, Italy, November 16-19, 2015

Roma Tre University, Italy

-

New York University, USA

-

University of Vigo, Spain

University of Geneva, Switzerland

TUE, The Netherlands

University of Kentucky, USA


Polytechnic Univ. of Milan, Italy


University of Campinas, Brasil

Morpho, France

Digimarc, USA

Univ. of Magdeburg, Germany

Michigan State University, USA

NTU, Singapore


Biometrics

Surveillance

Forensic Analysis

Hardware Security

Network Security

Adversarial Signal Processing

-Layer Security

Usability and Human Factors

Tutorial/special sessions proposals..

-

_______________
http://www.signalprocessingsociety.org/mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]://www.wifs2015.org/http://www.wifs2015.org/http://www.wifs2015.org/http://www.wifs2015.org/mailto:[email protected]:[email protected]:[email protected]://www.signalprocessingsociety.org/


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MAY 2015 VOLUME 17 NUMBER 5 ITMUF8 (ISSN 1520-9210)

PAPERS

Audio/Video Analysis and Synthesis

http://dx.doi.org/10.1109/TMM.2015.2412879. . . . . . . . . . . . . .. . . . . . ...................... S.-P. Lu, B. Ceulemans, A. Munteanu, and P. Schelkens 577Distributed and Parallel Processing

Networks http://dx.doi.org/10.1109/TMM.2015.2406574 . . . . . . . . . . . . . .. . . . . . . . . . . ... .. .. .. .. .. .. .. .. .. .. .. .. G. Dn, M. A. Khan, and V. Fodor 591

Multimodal Human-Human and Human-Computer Dialog

http://dx.doi.org/10.1109/TMM.2015.2407694 . . . . . .. . N. Harte and E. Gillen 603

Content Description and Annotation

http://dx.doi.org/10.1109/TMM.2015.2410734. . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. Pourian and B. S. Manjunath 616

http://dx.doi.org/10.1109/TMM.2015.2414720. . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Weng and J. Yuan 626

Multimedia Search and RetrievalFine-Grained Image Search http://dx.doi.org/10.1109/TMM.2015.2408566 . . . . . . . . . . . . .. ................ L. Xie, J. Wang, B. Zhang, and Q. Tian 636Fast Image Retrieval: Query Pruning and Early Termination http://dx.doi.org/10.1109/TMM.2015.2408563 . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L. Zheng, S. Wang, Z. Liu, and Q. Tian 648

http://dx.doi.org/10.1109/TMM.2015.2410135. . . . . . . . . . . . . .. . . . . . . . .. . .. .. .. . .. .. .. .. . .. .. X. Tan, F. Wu, X. Li, S. Tang, W. Lu, and Y. Zhuang 660 http://dx.doi.org/10.1109/TMM.2015.2413351 . . . . . . . . . . . .. . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . X. Li, M. Larson, and A. Hanjalic 674

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http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TMM.2015.2412879http://dx.doi.org/10.1109/TMM.2015.2406574http://dx.doi.org/10.1109/TMM.2015.2407694http://dx.doi.org/10.1109/TMM.2015.2410734http://dx.doi.org/10.1109/TMM.2015.2414720http://dx.doi.org/10.1109/TMM.2015.2408566http://dx.doi.org/10.1109/TMM.2015.2408563http://dx.doi.org/10.1109/TMM.2015.2410135http://dx.doi.org/10.1109/TMM.2015.2413351http://www.signalprocessingsociety.org/tmm/http://www.signalprocessingsociety.org/tmm/http://dx.doi.org/10.1109/TMM.2015.2412879http://dx.doi.org/10.1109/TMM.2015.2406574http://dx.doi.org/10.1109/TMM.2015.2407694http://dx.doi.org/10.1109/TMM.2015.2410734http://dx.doi.org/10.1109/TMM.2015.2414720http://dx.doi.org/10.1109/TMM.2015.2408566http://dx.doi.org/10.1109/TMM.2015.2408563http://dx.doi.org/10.1109/TMM.2015.2410135http://dx.doi.org/10.1109/TMM.2015.2413351http://www.signalprocessingsociety.org/


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Realtime Communication and Video Conferencing

http://dx.doi.org/10.1109/TMM.2015.2413354. . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . ... .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. S.-P. Chuah, Y.-P. Tan, and Z. Chen 687

Web and Internet

Semantic-Improved Color Imaging Applications: It Is All About Context http://dx.doi.org/10.1109/TMM.2015.2410175. . . . . . . . . . . . . . .. . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Lindner and S. Ssstrunk 700

Media Transmission and Communication Standardization

http://dx.doi.org/10.1109/TMM.2015.2416637. . . . . . . . . . . . .. . . . . . . . . . . . . .. . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Q. M. Qadir, A. A. Kist, and Z. Zhang 711

Media Cloud Computing and Communication

http://dx.doi.org/10.1109/TMM.2015.2416636. . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . .... ... ... ... ... ... ... .. ... ... ... ... . Z. Chang and S.-H. G. Chan 723

Wireless/Mobile Multimedia

Networks http://dx.doi.org/10.1109/TMM.2015.2408254 . . . . . . . . . . . . .. . . . . . . . .. .. .. .. .. .. .. .. .. .. A. Argyriou, D. Kosmanos, and L. Tassiulas 736

Multimodal Human Behavior

Automatic Recognition of Emergent Social Roles in Small Group Interactions http://dx.doi.org/10.1109/TMM.2015.2408437. . . . . . . . . . . . .. . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A.Sapru and H. Bourlard 746

Information for Authors http://dx.doi.org/10.1109/TMM.2015.2422256 . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . 761

CALLS FOR PAPERS

IEEE TRANSACTIONS ONCOMPUTATIONALIMAGING http://dx.doi.org/10.1109/TMM.2015.2422257 . . . . . . . . . . . . .. . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . 763IEEE TRANSACTIONS ONSIGNAL ANDINFORMATIONPROCESSINGONETWORKS http://dx.doi.org/10.1109/TMM.2015.2422258. . . . . . . . . 764
http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/TMM.2015.2413354http://dx.doi.org/10.1109/TMM.2015.2410175http://dx.doi.org/10.1109/TMM.2015.2416637http://dx.doi.org/10.1109/TMM.2015.2416636http://dx.doi.org/10.1109/TMM.2015.2408254http://dx.doi.org/10.1109/TMM.2015.2408437http://dx.doi.org/10.1109/TMM.2015.2422256http://dx.doi.org/10.1109/TMM.2015.2422257http://dx.doi.org/10.1109/TMM.2015.2422258http://dx.doi.org/10.1109/TMM.2015.2413354http://dx.doi.org/10.1109/TMM.2015.2410175http://dx.doi.org/10.1109/TMM.2015.2416637http://dx.doi.org/10.1109/TMM.2015.2416636http://dx.doi.org/10.1109/TMM.2015.2408254http://dx.doi.org/10.1109/TMM.2015.2408437http://dx.doi.org/10.1109/TMM.2015.2422256http://dx.doi.org/10.1109/TMM.2015.2422257http://dx.doi.org/10.1109/TMM.2015.2422258http://www.signalprocessingsociety.org/


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APRIL 2015 VOLUME 9 NUMBER 3 IJSTGY (ISSN 1932-4553)

ISSUE ON INTERACTIVE MEDIA PROCESSING FOR IMMERSIVE COMMUNICATION

EDITORIAL

Introduction to the Issue on Interactive Media Processing for Immersive Communication http://dx.doi.org/10.1109/JSTSP.2015.2406092 . . . ... .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . G. Cheung, D. Florencio, P. Callet, C.-W. Lin, and E. Magli 381

PAPERS

Single Shot Dual-Frequency Structured Light Based Depth Sensing http://dx.doi.org/10.1109/JSTSP.2015.2403794 . . . . . . . . . . . . .. . . . . . . . . . . . . ..... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... .. ... ... ... .. F. Li, S. Gao, G. Shi, Q. Li, L. Yang, R. Li, and X. Xie 384

Accurate Dynamic 3D Sensing With Fourier-Assisted Phase Shifting http://dx.doi.org/10.1109/JSTSP.2014.2378217 . . . . . . . . . . . .. . . . . . . . . . . . . ..... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... ... .. P. Cong, Z. Xiong, Y. Zhang, S. Zhao, and F. Wu 396

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____________________
http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/JSTSP.2015.2406092http://dx.doi.org/10.1109/JSTSP.2015.2403794http://dx.doi.org/10.1109/JSTSP.2014.2378217http://www.ieee.org/nondiscriminationhttp://www.ieee.org/sp/index.htmlhttp://www.ieee.org/sp/index.htmlhttp://dx.doi.org/10.1109/JSTSP.2015.2406092http://dx.doi.org/10.1109/JSTSP.2015.2403794http://dx.doi.org/10.1109/JSTSP.2014.2378217http://www.ieee.org/nondiscriminationhttp://www.signalprocessingsociety.org/


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Fast, Automated, Scalable Generation of Textured 3D Models of Indoor Environments http://dx.doi.org/10.1109/JSTSP.2014.2381153. . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . E. Turner, P. Cheng, and A. Zakhor 409

Large-Scale 3D Point Cloud Compression Using Adaptive Radial Distance Prediction in Hybrid Coordinate Domainshttp://dx.doi.org/10.1109/JSTSP.2014.2370752 . . . . . . . . . . . .. . . . . . . . . . . . ... .. .. .. .. .. .. .. .. .. .. .. .. J.-K. Ahn, K.-Y. Lee, J.-Y. Sim, and C.-S. Kim 422

http://dx.doi.org/10.1109/JSTSP.2014.2373331. . . . . . . . . . . . . .... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... .. ... .. ... .. ... ... ... ... ... ... ... . P. K. Rana, J. Taghia, Z. Ma, and M. Flierl 435

Real-Time and Temporal-Coherent Foreground Extraction With Commodity RGBD Camera http://dx.doi.org/10.1109/JSTSP.2014.2382476 . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M.Zhao, C.-W. Fu, J. Cai, and T.-J. Cham 449

Perceptual and Bitrate-Scalable Coding of Haptic Surface Texture Signals http://dx.doi.org/10.1109/JSTSP.2014.2374574 . . . . . . . . . . . . .. . . . . . . ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... ... R. Chaudhari, C. Schuwerk, M. Danaei, and E. Steinbach 462

http://dx.doi.org/10.1109/JSTSP.2015.2402633 . . . . . . . . . . . .. . . . . . . . . . . ......................... J. Chakareski, V. Velisavljevic, and V. Stankovic 474

http://dx.doi.org/10.1109/JSTSP.2015.2407320 . . . . . . . . . . . .. . . . . . . . . . . . . .. . .. .. .. .. .. .. .. .. .. .. .. .. .. .. A. De Abreu, P. Frossard, and F. Pereira 487

Streaming Codes With Partial Recovery Over Channels With Burst and Isolated Erasures http://dx.doi.org/10.1109/JSTSP.2014.2388191. . . ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... .. ... ... ... ... ... ... ... . A. Badr, A. Khisti, W. Tan, and J. Apostolopoulos 501

Cloud Mobile 3D Display Gaming User Experience Modeling and Optimization by Asymmetric Graphics Renderinghttp://dx.doi.org/10.1109/JSTSP.2015.2396475 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . .... ... ... ... ... ... ... ... ... ... ... ... Y. Lu, Y. Liu, and S. D. Dey 517

3D Perception Based Quality Pooling: Stereopsis, Binocular Rivalry, and Binocular Suppression

http://dx.doi.org/10.1109/JSTSP.2015.2393296 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Lee and S. Lee 533ITEM: Immersive Telepresence for Entertainment and MeetingsA Practical Approach http://dx.doi.org/10.1109/JSTSP.2014.2375819. . . . .................................................. V. A. Nguyen, J. Lu, S. Zhao, D. T. Vu, H. Yang, D. L. Jones, and M. N. Do 546

withyou http://dx.doi.org/10.1109/JSTSP.2015.2402635 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. J. Roberts,

A. J. Fairchild, S. P. Campion, J. OHare, C. M. Moore, R. Aspin, T. Duckworth, P. Gasparello, and F. Tecchia 562
http://www.signalprocessingsociety.org/http://dx.doi.org/10.1109/JSTSP.2014.2381153http://dx.doi.org/10.1109/JSTSP.2014.2370752http://dx.doi.org/10.1109/JSTSP.2014.2373331http://dx.doi.org/10.1109/JSTSP.2014.2382476http://dx.doi.org/10.1109/JSTSP.2014.2374574http://dx.doi.org/10.1109/JSTSP.2015.2402633http://dx.doi.org/10.1109/JSTSP.2015.2407320http://dx.doi.org/10.1109/JSTSP.2014.2388191http://dx.doi.org/10.1109/JSTSP.2015.2396475http://dx.doi.org/10.1109/JSTSP.2015.2393296http://dx.doi.org/10.1109/JSTSP.2014.2375819http://dx.doi.org/10.1109/JSTSP.2015.2402635http://dx.doi.org/10.1109/JSTSP.2014.2381153http://dx.doi.org/10.1109/JSTSP.2014.2370752http://dx.doi.org/10.1109/JSTSP.2014.2373331http://dx.doi.org/10.1109/JSTSP.2014.2382476http://dx.doi.org/10.1109/JSTSP.2014.2374574http://dx.doi.org/10.1109/JSTSP.2015.2402633http://dx.doi.org/10.1109/JSTSP.2015.2407320http://dx.doi.org/10.1109/JSTSP.2014.2388191http://dx.doi.org/10.1109/JSTSP.2015.2396475http://dx.doi.org/10.1109/JSTSP.2015.2393296http://dx.doi.org/10.1109/JSTSP.2014.2375819http://dx.doi.org/10.1109/JSTSP.2015.2402635http://www.signalprocessingsociety.org/


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ICASSP2016: Signal and information processing is the driving heartbeat in the developmentof technologies that enrich our lives and advance our society. The 41st InternationalConference on Acoustics, Speech, and Signal Processing (ICASSP) will be held in theShanghai International Convention Center, Shanghai, China between March 20 and 25,2016. The conference provides, both for researchers and developers, an engaging forum toexchange ideas and propel new developments in this field. The 2016 conference willshowcase world-class presentations by internationally renowned speakers and will facilitate afantastic opportunity to network with like-minded professionals from around the world.Topics include but are not limited to:

Multimedia signal processingSensor array & multichannel signal processing

Design & implementation of signal processing systemsSignal processing for communications & networkingImage, video & multidimensional signal processing

Signal processing theory & methodsSpoken language processingSignal processing for the Internet of Things

Audio and acoustic signal processingBio-imaging and biomedical signal processing

Signal processing educationSpeech processingIndustry technology tracks

Information forensics and securityMachine learning for signal processing

Signal processing for Big Data

Submission of Papers: Prospective authors are invited to submit full-length papers, withup to four pages for technical content including figures and possible references, and with oneadditional optional 5th page containing only references. A selection of best student paperswill be made by the ICASSP 2016 committee upon recommendations from the Technical

Committees.

Tutorial and Special Session Proposals: Tutorials will be held on March 20 and 21, 2016.Tutorial proposals must include title, outline, contact information, biography and selectedpublications for the presenter(s), and a description of the tutorial and the material to bedistributed to participants. Special session proposals must include a topical title, rationale,session outline, contact information, and a list of invited speakers. Additional information canbe found at the ICASSP 2016 website.

Signal Processing Letters: Authors of IEEE Signal Processing Letters (SPL) papers will begiven the opportunity to present their work at ICASSP 2016, subject to space availability andapproval by the ICASSP Technical Program Chairs. SPL papers published between January 1,2015 and December 31, 2015 are eligible for presentation at ICASSP 2016.

Show and Tell: S&T offers a perfect stage to showcase innovative ideas in all technicalareas of interest at ICASSP. S&T sessions contain demos that are highly interactive andvisible. Please refer to the ICASSP 2016 website for additional information regarding demosubmission.

Important Deadlines:Special session & tutorial proposals August 3, 2015Notification of special session & tutorial acceptance ... September 11, 2015Submission of regular papers .. September 25, 2015Signal processing letters .. December 16, 2015Notification of paper acceptance December 21, 2015Revised paper upload . January 22, 2016Author registration ... January 22, 2016

Shanghai: Shanghai is the most populous city in China and one of the most populous citiesin the world. A global city, Shanghai exerts influence over global commerce, finance, culture,

art, fashion, research and entertainment. The city is located in the middle portion of theChinese coast, and sits at the mouth of the Yangtze River. The city is a tourist destinationrenowned for its historical landmarks, such as the Bund and City God Temple, and itsmodern and ever-expanding Pudong skyline including the Oriental Pearl Tower. Today,Shanghai is the largest center of commerce and finance in mainland China, and has beendescribed as the "showpiece" of the world's fastest-growing major economy.

General ChairsZhi Ding, Univ. of California, Davis, USA

Zhi-Quan Luo, Univ. of Minnesota, USAWenjun Zhang, Shanghai Jiao Tong Univ., China

Technical Program ChairsP. C. Ching, Chinese Univ. of Hong Kong, HongKongDominic K.C. Ho, Univ. of Missouri, USA

Finance ChairsShuguang Cui, Texas A&M Univ., USARong Xie, Shanghai Jiao Tong Univ., China

Plenaries ChairsZhi-Pei Liang, UIUC, USABjrn Ottersten, Univ. of Luxembourg, Luxembourg

Special Sessions ChairsTim Davidson, McMaster Univ., Canada

Jianguo Huang, Northwestern Polytech. Univ., China

Tutorials ChairsJian Li, Univ. of Florida, USAJose Principe, Univ. of Florida, USA

Student Session Chair

Wei Zhang, Univ. of New South Wales, AustraliaRegistration ChairsTongtong Li, Michigan State Univ., USAXiaojun Yuan, ShanghaiTech Univ., China

Publicity ChairsXiaokang Yang, Shanghai Jiao Tong Univ., China

Mounir Ghogho, Leeds Univ., UKIgnacio Santamaria, Univ. of Cantabria, Spain

Publication Chairs

Min Dong, Univ. of Ontario Inst. of Tech., CanadaThomas Fang Zheng, Tsinghua Univ., China

Industrial & Exhibit ChairsLi Deng, Microsoft, USAJinyu Li, Microsoft, USACathy Wicks, Texas Instruments, USA

Local Arrangement ChairsNing Liu, Shanghai Jiao Tong Univ., China

Meixia Tao, Shanghai Jiao Tong Univ., China

Webmaster

Yi Xu, Shanghai Jiao Tong Univ., China

Workshop ChairsJianguo Huang, Northwestern Polytech. Univ., ChinaJiwu Huang, Sun Yat-sen Univ., China
http://www.signalprocessingsociety.org/http://www.signalprocessingsociety.org/


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JUNE 2015 VOLUME 22 NUMBER 6 ISPLEM (ISSN 1070-9908)

LETTERS

Color Cat: Remembering Colors for Illumination Estimation http://dx.doi.org/10.1109/LSP.2014.2366973. . . . .. .. N. Banicand S. Loncaric 651Distributed Energy Beamforming for Simultaneous Wireless Information and Power Transfer in the Two-Way Relay

Channel http://dx.doi.org/10.1109/LSP.2014.2365718. . . . . . . . . . . .. . . . . . . . . . . . . .. . . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. . Z. Fang, X. Yuan, and X. Wang 656Effective Estimation of Node-to-Node Correspondence Between Different Graphs http://dx.doi.org/10.1109/LSP.2014.2366051 . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . H. Jeong and B.-J. Yoon 661An EEG-Based Biometric System Using Eigenvector Centrality in Resting State Brain Networks

http://dx.doi.org/10.1109/LSP.2014.2367091. . . . . . . . . . . ........... M. Fraschini, A. Hillebrand, M. Demuru, L. Didaci, and G. L. Marcialis 666

http://dx.doi.org/10.1109/LSP.2014.2365393

. . . . . . . . . . . .. . . . . . . . . . . ... .. .. .. .. .. .. .. .. .. .. .. H. Kaya, T. zkaptan, A. A. Salah, and F. Grgen 671Greedy Reduction Algorithms for Mixtures of Exponential Family http://dx.doi.org/10.1109/LSP.2014.2367154 . . . . . . . . . . . . . .. . . . . . . . . . . . .. . . ... ... ... ... ... ... .. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... . T. Ardeshiri, K. Granstrm, E. zkan, and U. Orguner 676

Source Separation of Multimodal Data: A Second-Order Approach Based on a Constrained Joint Block Decompositionof Covariance Matrices http://dx.doi.org/10.1109/LSP.2014.2367158. . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Rivet 681

Salient Region Detection Using Patch Level and Region Level Image Abstractions http://dx.doi.org/10.1109/LSP.2014.2366192. . . . . . . . . . . . .................................................................................... R. Kannan, G. Ghinea, and S. Swaminathan 686

Extracting Electrical Network Frequency From Digital Recordings Using Frequency Demodulationhttp://dx.doi.org/10.1109/LSP.2014.2368516 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L. Dosiek 691

Networks http://dx.doi.org/10.1109/LSP.2014.2368253 . . . . . . . . . . . .. . . . . . ... .. .. .. .. .. .. .. .. . N. K. D. Venkategowda and A. K. Jagannatham 696

Design of Near Orthogonal Graph Filter Banks http://dx.doi.org/10.1109/LSP.2014.2368128 . . . . . . . . . . . . . .. .. .. .. .. .. . D. B. H. Tay and Z. Lin 701

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Perceptual Relevance Based Image Retargeting http://dx.doi.org/10.1109/LSP.2014.2368136 . . . . . ..... U. Engelke, J. Wang, and P. Marendy 705On the Convergence of Maronnas -Estimators of Scatter http://dx.doi.org/10.1109/LSP.2014.2367547 . . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Y. Chitour, R. Couillet, and F. Pascal 709A Tunable W-ABORT-Like Detector with Improved Detection vs Rejection Capabilities Trade-Off

http://dx.doi.org/10.1109/LSP.2014.2364395 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . .... .. ... ... ... ... ... ... ... ... ... ... ... A. Coluccia and G. Ricci 713Fast Computation of Discrete Optimal FIR Estimates in White Gaussian Noise http://dx.doi.org/10.1109/LSP.2014.2368777 . . . . . . . . . . . . .. . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Zhao, Y. S. Shmaliy, and F. Liu 718Robust AN-Aided Secure Transmission Scheme in MISO Channels with Simultaneous Wireless Information and Power

Transfer http://dx.doi.org/10.1109/LSP.2014.2368695. . . . . . . . . . . . .. . . . . . . . . . ... .. .. .. .. .. .. .. .. .. .. .. M. Tian, X. Huang, Q. Zhang, and J. Qin 723A Zoned Image Patch Permutation Descriptor http://dx.doi.org/10.1109/LSP.2014.2352172. . . . . .. . . . . T. Tian, I. Sethi, D. Ming, and N. Patel 728Robust Pilot Detection Techniques for Channel Estimation and Symbol Detection in OFDM Systems

http://dx.doi.org/10.1109/LSP.2014.2364924 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . ........................................ H. Zhang and H.-C. Wu 723Receive Antenna Selection for Underlay Cognitive Radio with Instantaneous Interference Constraint

http://dx.doi.org/10.1109/LSP.2014.2363163 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. M. Hanif, H.-C. Yang, and M.-S. Alouini 738 http://dx.doi.org/10.1109/LSP.2014.2368952. . . . . . . .

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. . M. Higger, M. Akcakaya, H. Nezamfar, G. LaMountain, U. Orhan, and D. Erdogmus 743High-Precision, Permanently Stable, Modulated Hopping Discrete Fourier Transform http://dx.doi.org/10.1109/LSP.2014.2369518. . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Q. Wang, X. Yan, and K. Qin 748Non-Coherent Unambiguous Tracking Method for Cosine-BOC Signals Based on an S-Curve Shaping Technique

http://dx.doi.org/10.1109/LSP.2014.2368951 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . .... .. ... ... ... ... ... ... ... ... ... ... ... F. Shen, G. Xu, and Q. Li 752Estimating Effective Connectivity from fMRI Data Using Factor-based Subspace Autoregressive Modelshttp://dx.doi.org/10.1109/LSP.2014.2365634 . . . . . . . . . . . .. . . . . . .. .. .. .. . .. .. .. . .. .. C.-M. Ting, A.-K. Seghouane, S.-H. Salleh, and A. M. Noor 757

http://dx.doi.org/10.1109/LSP.2014.2369212 . .................................................... E. Bostan, S. Lefkimmiatis, O. Vardoulis, N. Stergiopulos, and M. Unser 762

http://dx.doi.org/10.1109/LSP.2014.2358625 . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Ma, Y. Ma, J. Zhao, and J. Tian 767

Reduced-Complexity Super-Resolution DOA Estimation with Unknown Number of Sources http://dx.doi.org/10.1109/LSP.2014.2368987 . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. V. Reddy, M. Mubeen, and B. P. Ng 772

On the Expected Likelihood Approach for Assessment of Regular

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