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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao IEEE Signal Processi...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
IEEE Signal Processing Letters
Article . 2010 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Improved Context-Based Adaptive Binary Arithmetic Coding over H.264/AVC for Lossless Depth Map Coding

Authors: null Jin Heo; null Yo-Sung Ho;

Improved Context-Based Adaptive Binary Arithmetic Coding over H.264/AVC for Lossless Depth Map Coding

Abstract

The depth map, which represents three-dimensional (3D) information, is used to synthesize virtual views in the depth image-based rendering (DIBR) method. Since the quality of synthesized virtual views highly depends on the quality of depth map, we encode the depth map under the lossless coding mode. The original context-based adaptive binary arithmetic coding (CABAC) that was originally designed for lossy texture coding cannot provide the best coding performance for lossless depth map coding due to the statistical differences of residual data in lossy and lossless depth map coding. In this letter, we propose an enhanced CABAC coding mechanism for lossless depth map coding based on the statistics of residual data. Experimental results show that the proposed CABAC method provides approximately 4% bit saving compared to the original CABAC in H.264/AVC.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Average
Top 10%
Top 10%
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