Improved Distributed Compressive Sensing Basing on HEVC ME and BM3D-AMP Algorithm
The distributed compressive video sensing (DCVS) system greatly reduces the pressure on the encoder by transferring the computational complexity to the decoder, which is suitable for the limited-resource video sensing and transmission environment, in the meantime, get the better performance from key (K) frames and non-key (CS) frames. In this paper, we use the approximate message passing (AMP) algorithm reconstruct the K-frames. In order to improve the quality of the reconstructed K-frames, we add the block-matching 3D filtering (BM3D) denoising strategy based on the AMP algorithm. For the CS-frames, we improve the reconstructed CS-frames by improving the accuracy of side information (SI) frames by proposing a new high efficiency video coding (HEVC) motion estimation (ME) algorithm with motion vector (MV) prediction method. After we obtain the SI frames and combine the compressed value of the CS-frames with the side information (SI) fusion algorithm based on the difference compensation algorithm, the high accuracy SI frame is integrated into the reconstruction algorithm of the CS-frames. The experimental results demonstrate that our algorithms achieve higher subjective visual quality and peak signal-to-noise ratio than the traditional methods.
KeywordsDistributed compressive video sensing High efficiency video coding Approximate message passing Block-matching 3D filtering
This work was supported in part by the National Natural Science Foundation of China under Grant 61371102, 61771158 and in part by the Shenzhen Municipal Science and Technology Plan under Grant JCYJ20170811160142808, JCYJ20170811154309920.
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