Fast motion estimation and mode decision for H.264 video coding in packet loss environment
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Fast motion estimation and mode decision for H.264 video coding in packet loss environment Li Liu, Xinhua Zhuang Computer Science Department, University of Missouri-Columbia, USA IEEE ICME(International Conference on Multimedia & Expo) 2008 June 2008 Presenter : SeungDae Jeong
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Presenter : SeungDae Jeong. Fast motion estimation and mode decision for H.264 video coding in packet loss environment. Li Liu, Xinhua Zhuang Computer Science Department, University of Missouri-Columbia, USA IEEE ICME(International Conference on Multimedia & Expo) 2008 June 2008. - PowerPoint PPT Presentation
Transcript of Fast motion estimation and mode decision for H.264 video coding in packet loss environment
Fast motion estimation and mode decisionfor H.264 video coding in packet loss environment
Li Liu, Xinhua Zhuang
Computer Science Department, University of Missouri-Columbia, USA
IEEE ICME(International Conference on Multimedia & Expo) 2008
June 2008
Presenter : SeungDae Jeong
IntroductionIntroduction
Packet loss environment Practical video communications Videos are usually coded without considering varying channel
conditions Error propagation
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IntroductionIntroduction
“Intra refresh” algorithm Using intra frames that doesn't refer to previous frames
The decision of intra mode Rate distortion optimization
• Quantization distortion• Channel distortion
Simulation based estimation Model based estimation
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Previous frame Inter framewith packet loss
Intra frame
ContentsContents
RD Optimized intra fresh for error resilience Lagrange Cost Function in Packet Loss Environment Model Based Channel Distortion Estimation
Use channel distortion map for fast mode decision and motion estimation
Channel distortion map based fast mode decision and motion estimation algorithm Fast Mode Decision Fast Motion Estimation
Experiment results
Conclusion
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Lagrange Cost Function in Packet Loss EnvironmentLagrange Cost Function in Packet Loss Environment
Set of all defined coding options for macroblock m in frame n
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The source distortion by quantization
The result bit rate
The relation between distortion and bit rate
Lagrange Cost Function in Packet Loss EnvironmentLagrange Cost Function in Packet Loss Environment
In packet loss environment
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The quantization distortion
The error concealment distortionwhen a macrobloak is lost
The error propagation distortionif reference frames in motion estimation are erroneous
The estimated channel packet loss rate
Lagrange Cost Function in Packet Loss EnvironmentLagrange Cost Function in Packet Loss Environment
The modified Lagrange cost function for RD optimization mode decision
The rate distortion cost for intra mode
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Model Based Channel Distortion EstimationModel Based Channel Distortion Estimation
Define a channel distortion map on 4x4 block basis To track potential error propagation
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Model Based Channel Distortion EstimationModel Based Channel Distortion Estimation
Block based channel distortion map
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The optimal mode decision
The error propagation distortion of ith block
The error concealment distortion
The estimated error propagation distortion
Use channel distortion mapUse channel distortion mapfor fast mode decision and motion estimationfor fast mode decision and motion estimation
The error propagation distortion tends to surpass the quantization distortion as
• frames contain more motions (e.g., from frame 150 to 250)• loss rate increases (e.g., from 0.05 to 0.10)
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Use channel distortion mapUse channel distortion mapfor fast mode decision and motion estimationfor fast mode decision and motion estimation
Statistical information from coded video sequence using original MBDE algorithm
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Channel distortion map basedChannel distortion map basedfast mode decision and motion estimation algorithmfast mode decision and motion estimation algorithm
Fast mode decision Computational cost of estimating Dep(o) is quite small By using Dep(o) as assistance to decide early termination of possible
inter coding choices, encoding speed can be accelerated significantly
Fast Motion Estimation Choosing the best motion vector Minimizing a Lagrange cost function
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Fast mode decisionFast mode decision
Computational cost Inter coding cost > Intra coding cost
The calculation of minDep Dependent on optimal motion vector decision from motion
estimation process Computational cost can not be reduced
Computing Dep(o) based on the predicted motion vector
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Fast mode decisionFast mode decision
Computing Dep(o) based on the predicted motion vector
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Fast motion estimationFast motion estimation
Minimizing a Lagrange cost function
Fast motion estimation algorithm selects best motion vector from a set of candidates, and terminates those macroblocks that may have large error propagation distortion associated
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The sum of absolute difference
The number of bits to code motion information
Fast motion estimationFast motion estimation
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Experiment resultsExperiment results
Implemented using H.264 reference software JM12.1 http://iphome.hhi.de/suehting/tml/download/old_jm/
Video sequences Carphone, Foreman, Coastguard
QCIF format, 7.5 fps Fixed quantization parameter (QP)
Packet loss simulation S. Wenger, “Internet Error Patterns”
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Experiment resultsExperiment results
PSNR Peak Signal-to-Noise Ratio
Bit rate
Speed Very fast
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ConclusionConclusion
Two stage fast mode decision and motion estimation algorithm for H.264 video coding in packet loss environment
Advantage of estimated channel distortion as assistance to decide early termination of possible inter coding options
Reduce coding complexity significantly while maintaining similar average picture quality
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