2010IEEE Signal Processing LettersRequires access

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

Jin Heo, Yo-Sung Ho

Open publisher page 18 citations

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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What this paper is about

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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Available 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.

Key concepts: Context-adaptive variable-length coding, Context-adaptive binary arithmetic coding, Arithmetic coding, Tunstall coding, Lossless compression, Computer science, Lossy compression, Coding tree unit

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