Compressive sensing reconstruction via decomposition
作者：
Highlights：
• Image features (edge, smooth, texture regions) have different characteristics.
• A decomposition based CS reconstruction is proposed via denoising filters.
• An instance of image denoise boosting techniques in CS reconstruction.
• The better recovery and filter methods, the higher performance is archived.
• Multiple image priors improve the final CS reconstruction performance.
摘要
Highlights•Image features (edge, smooth, texture regions) have different characteristics.•A decomposition based CS reconstruction is proposed via denoising filters.•An instance of image denoise boosting techniques in CS reconstruction.•The better recovery and filter methods, the higher performance is archived.•Multiple image priors improve the final CS reconstruction performance.
论文关键词：Compressive sensing,Image decomposition,Total variation,Nonlocal structure,Split Bregman
论文评审过程：Received 26 March 2016, Revised 17 October 2016, Accepted 17 October 2016, Available online 19 October 2016, Version of Record 28 October 2016.
论文官网地址：https://doi.org/10.1016/j.image.2016.10.001
