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Conventional Image Enhancement to

High Dynamic Range Image Enhancement

Assoc. Prof. Dr. Gholamreza Anbarjafari

Shahab iCV Research Group

Image Enhancement Resolution Enhancement Illumination Enhancement

Denoising

• In visual perception of the real world, contrast is determined by the difference in the color and brightness of the object with other objects in the same field of view. • The human visual system is more sensitive to contrast than absolute luminance; hence, we can perceive the world similarly regardless of the considerable changes in illumination conditions.

A face image from the CALTECH face database (a), its histogram (b), the equalized face image using GHE (c) and its respective histogram (d).

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(b)(a)

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ILLUMINATION

(a)(b)

A face image from the CALTECH face database (a), and the equalized face image using histogram equalization in each R, G, and B channels separately (b).

SINGULAR VALUE DECOMPOSITION

TA A AA U V= Σ

where UA and VA are orthogonal square matrices known as hanger and aligner respectively, and ΣA matrix contains the sorted singular values on its main diagonal.

ΣA contains the intensity information of the given image

(a) (b)

(c) (d)

(e) (f)

(g) (h)

 

A grey scale image (a) and the effect of changing the σ1: σ1=0 (b), σ1= σ1+3√σ1 (c), σ1= σ1-3√σ1 (d), σ1= σ1+10√σ1 (e), σ1= σ1-10√σ1 (f), σ1= σ1+0.75σ1 (g), and σ1= σ1-0.75σ1 (h).

SVD BASED EQUALİZATİON: SVE

= ΣT

A A AA U V

( )( )( )µ

ξ= =Σ

=Σ

0,var 1max

maxN

A

( )ξΞ = Σ Tequalized A A AA U V

SVE

(a)

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(e)

(b)

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(f)

(c)

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(d)

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A face image from Caltech database (a), introduced low density of the same image (b) and the resultant image of SVE (c) and GHE (d) and

their respective smoothed histograms (e)-(h).

WAvelet

Discrete Wavelet Transform Single Tree Complex Wavelet Transform Dual Tree Complex Wavelet Transform

1 Level DWT

DWT

DWT+SVE LL subband concentrates the illumination information

There are two significant parts of the proposed method: • The first one is the use of SVD. Changing singular values will directly affect the illumination of the image hence the other information in the image will not be changed. • The second important aspect of this work is the application of DWT.

DWT+SVE

Low contrast input satellite image

Equalized image using GHE

DWT DWT

LLLHHLHH HHHLLHLL

Calculate the U, Σ, and V for LL subband image and find the maximum element in Σ.

Calculate the U, Σ, and V for LL subband image and find the maximum element in Σ.

Calculate ζusing Eq (4)

Calculate the new Σ and reconstruct the new LL image, by using Eq (6).

IDWT

Equalized satellite image

ζ =

max ΣLLA( )max ΣLLA( )

ζΣ

= Σ

= Σ

LL LL

LL LL

LLA

A ALL U VAA A

DWT+SVE

(a) (b) (c)

(d) (e) (f)

  Original low contrast images from Antarctic Meteorological Research Centre (a), equalized image by using: GHE (b), LHE (c), SVE (d), BPDHE (e), and proposed technique (f).

DWT+SVE

(a) (b) (c)

(d) (e) (f)

 Original low contrast image from Satellite imaging Corporation (a), equalized image by using: GHE (b), LHE (c), SVE (d), BPDHE (e), and proposed technique (f).

PUblished Work 1.  Demirel, H., & Anbarjafari, G. (2008). Pose invariant face

recognition using probability distribution functions in different color channels. Signal Processing Letters, IEEE, 15, 537-540.

2.  Demirel, H., Anbarjafari, G., & Jahromi, M. N. S. (2008, October). Image equalization based on singular value decomposition. In Computer and Information Sciences, 2008. ISCIS'08. 23rd International Symposium on (pp. 1-5). IEEE.

3.  Demirel, H., Ozcinar, C., & Anbarjafari, G. (2010). Satellite image contrast enhancement using discrete wavelet transform and singular value decomposition. Geoscience and Remote Sensing Letters, IEEE, 7(2), 333-337.

4.  Anbarjafari, G., Jafari, A., Jahromi, M. N. S., Ozcinar, C., & Demirel, H. (2015). Image illumination enhancement with an objective no-reference measure of illumination assessment based on Gaussian distribution mapping. Engineering Science and Technology, an International Journal, 18(4), 696-703.

PUblished Work 5.  Ozcinar, C., Demirel, H., & Anbarjafari, G. (2011). Image Equalization

Using Singular Value Decomposition and Discrete Wavelet Transform. Discrete Wavelet Transforms: Theory and Applications, 87-94.

6.  Anbarjafari, G., Izadpanahi, S., & Demirel, H. (2015). Video resolution enhancement by using discrete and stationary wavelet transforms with illumination compensation. Signal, Image and Video Processing, 9(1), 87-92.

7.  Demirel, H., Anbarjafari, G., Ozcinar, C., & Izadpanahi, S. (2011, September). Video resolution enhancement by using complex wavelet transform. In Image Processing (ICIP), 2011 18th IEEE International Conference on (pp. 2093-2096). IEEE.

HDR •  High Dynamic Range Imaging •  10-12-14-16-… bits •  Displays are conventional 8-10 bits •  Standards?

HDR •  Collaborative work with Telecom

ParisTech for ICIP2016

•  Adaptive HDR display

•  Reduction of flickers

HDR •  Demo 1

•  Demo 2

HDR

Thank You