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

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.