Side Information Generation Algorithm Based on Weighted KSVD Dictionary

The side information plays an important role in video reconstruction for distributed compressed video sensing. In this paper, we propose a novel weighted KSVD dictionary learning based side information extraction method. First, the similarity between the non-key frame and its neighboring key frames is calculated in the measurement domain. According to the calculated similarities, different weighted factors are allocated to the motion estimation module to generate the side information. Then the dictionary is generated by the side information and KSVD algorithm. The simulation results show that the proposed algorithm outperforms the existed non-weighted side information algorithm in terms of peak-signal-to-noise ratio (PSNR) by 0.2–0.5 dB and visual perception.

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