Blind compressive sensing using block sparsity and nonlocal low-rank priors

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• 作者：Lei Feng ^{fenglei492327278@126.com} ; Huaijiang Sun ; ^{sunhuaijiang@njust.edu.cn} ; Quansen Sun ; Guiyu Xia
• 关键词：Blind compressive sensing ; Nonlocal low-rank regularization ; Nuclear norm ; Alternating direction method of multipliers
• 刊名：Journal of Visual Communication and Image Representation
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：42
• 期：Complete
• 页码：37-45
• 全文大小：1292 K
• 卷排序：42

文摘

A novel BCS method using block sparisty and nonlocal low-rank priors is proposed. The images in our model are divided into overlapping blocks to reduce artifacts. ADMM can efficiently solve the resulting complicated optimization problem. Our model can greatly reduce the sampling rate without sacrificing the quality.