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About the code

This is the matlab implementation of the paper "Zhao, C., Ma, S., Zhang, J., Xiong, R., & Gao, W. (2017). Video compressive sensing reconstruction via reweighted residual sparsity. IEEE Transactions on Circuits and Systems for Video Technology, 27(6), 1182-1195." [Click here for the paper]

Usage

  1. Uncompress the .rar file dependencies/mh-bcs-spl-1.0-1.rar into the folder Phase1_intra/Utilities/
  2. Run Phase1_intra/Demo.m to generate the intial recovery for all frames;
  3. Run Phase2_inter/Demo.m to apply inter RRS to further enhance the quality of nonkey frames.

Cite this work

Please cite the following paper if you use this code.

@article{zhao2017video,
  title={Video compressive sensing reconstruction via reweighted residual sparsity},
  author={Zhao, Chen and Ma, Siwei and Zhang, Jian and Xiong, Ruiqin and Gao, Wen},
  journal={IEEE Transactions on Circuits and Systems for Video Technology},
  volume={27},
  number={6},
  pages={1182--1195},
  year={2017},
  publisher={IEEE}
}

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Matlab implementation of the CS video reconstruction method RRS

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