南京理工大学学报（自然科学版）2017，Vol.41Issue(4)：399-404,6.DOI:10.14177/j.cnki.32-1397n.2017.41.04.001
结合局部稀疏性和非局部相似性的盲压缩感知方法
Blind compressive sensing method via local sparsity and nonlocal similarity
封磊 1孙怀江1
作者信息
- 1. 南京理工大学 计算机科学与工程学院,江苏 南京 210094
- 折叠
摘要
Abstract
In order to reduce the sampling rate of the traditional blind compressive sensing image recovery method,this paper proposes a novel blind compressive sensing image recovery approach.The method simultaneously exploits the local patch sparsity and nonlocal patch similarity.In addition,it employs an alternating direction method of multipliers to solve the resulting non-convex optimization problem.The method can accurately recover the original image.Experimental results have demonstrated that the proposed method can significantly reduce the sampling rate without sacrificing the quality of the reconstructed image.关键词
盲压缩感知/稀疏表示/字典学习/非局部相似性/交替方向乘子法Key words
blind compressive sensing/sparse representation/dictionary study/nonlocal similarity/alternating direction method of multipliers分类
信息技术与安全科学引用本文复制引用
封磊,孙怀江..结合局部稀疏性和非局部相似性的盲压缩感知方法[J].南京理工大学学报（自然科学版）,2017,41(4):399-404,6.
