|Table of Contents|

Blind compressive sensing method via local sparsity and nonlocal similarity(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2017年04期
Page:
399-
Research Field:
Publishing date:

Info

Title:
Blind compressive sensing method via local sparsity and nonlocal similarity
Author(s):
Feng LeiSun Huaijiang
School of Computer Science and Engineering,Nanjing University of Science and Technology,Nanjing 210094,China
Keywords:
blind compressive sensing sparse representation dictionary study nonlocal similarity alternating direction method of multipliers.
PACS:
TN911.72
DOI:
10.14177/j.cnki.32-1397n.2017.41.04.001
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.

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Last Update: 2017-08-31