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A Low Complexity Compressed Sensing-Based Codec for Consumer Depth Video Sensors

2019; Institute of Electrical and Electronics Engineers; Volume: 65; Issue: 4 Linguagem: Inglês

10.1109/tce.2019.2929586

1558-4127

Shengwei Wang, Li Yu, Sen Xiang,

Sparse and Compressive Sensing Techniques

In 3-D applications, a high-quality depth video codec with low complexity is in great demand for consumer devices, which generally have limited computational resources and energy. Based on the compressed sensing theory, we propose a low complexity depth video codec to compress depth videos effectively. The proposed codec decomposes depth blocks via an adaptive wavelet decomposition algorithm by following the principle of local entropy minimization. The decomposition can reduce the amount of local data, and separate depth blocks by frequency precisely. In order to reduce temporal redundancy, a block average value-based fast motion estimation scheme is also designed. Further, a joint optimization method is proposed to select the best combination of quantization parameter and measurement rate for each block. The experimental results demonstrate that the proposed codec, compared with H.265 and H.264, achieves BD-PSNR improvement up to 1.34 dB and 4.28 dB at most respectively in "AllIntra" mode. In "IPPP" mode, the proposed codec also achieves BD-PSNR improvement up to 0.62 dB and 1.79 dB on average respectively. Moreover, compared with other methods, the complexity and energy consumption of the proposed codec is much lower, which is adapted to consumer devices well.