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Local entropy minimization and measurement rate allocation for compressed sensing of depth video | IEEE Conference Publication | IEEE Xplore

Local entropy minimization and measurement rate allocation for compressed sensing of depth video


Abstract:

Compressed sensing (CS) provides a new method to encode depth videos, which utilizes the sparsity of depth maps to improve the coding efficiency. In this paper, we design...Show More

Abstract:

Compressed sensing (CS) provides a new method to encode depth videos, which utilizes the sparsity of depth maps to improve the coding efficiency. In this paper, we design a novel CS-based depth video codec. The codec adaptively decomposes blocks from 64 χ 64 to 8 χ 8 sub-blocks via wavelet transforming. The decomposition divides smooth regions and complex boundaries by frequencies, and minimizes the local entropy of sub-blocks. Moreover, a measurement rate allocation algorithm is also proposed, which utilizes the rate-distortion optimization (RDO) to allocate the measurement rate for each block. The experimental results demonstrate that, compared with H.264/AVC and H.265/HEVC, the proposed codec improves the quality of virtual views by 1-2 dB and 0.2-0.5 dB PSNR respectively. Meanwhile, the codec reduces coding complexity greatly.
Date of Conference: 04-07 December 2016
Date Added to IEEE Xplore: 24 April 2017
ISBN Information:
Electronic ISSN: 2472-7822
Conference Location: Nuremberg, Germany

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