Block compressive sensing of image and video with nonlocal Lagrangian multiplier and patch-based sparse representation
作者：
Highlights：
• Multi-block gradient to reduce blocking artifacts by block-independent TV recovery.
• Lagrangian multiplier denoised directly by the nonlocal means filter.
• Low contrast details enhanced by patch-based sparse representation.
• Global and local sparsifying transforms to enhance sparsity level of noisy data.
• Extension to a block compressive video sensing problem (DCVS).
摘要
Highlights•Multi-block gradient to reduce blocking artifacts by block-independent TV recovery.•Lagrangian multiplier denoised directly by the nonlocal means filter.•Low contrast details enhanced by patch-based sparse representation.•Global and local sparsifying transforms to enhance sparsity level of noisy data.•Extension to a block compressive video sensing problem (DCVS).
论文关键词：Block compressive sensing,Distributed compressive video sensing,Total variation,Nonlocal means filter,Sparsifying transform
论文评审过程：Received 26 March 2016, Revised 28 February 2017, Accepted 28 February 2017, Available online 2 March 2017, Version of Record 14 March 2017.
论文官网地址：https://doi.org/10.1016/j.image.2017.02.012
