Fletcher-Reeves Conjugate Gradient for Sparse Reconstruction：Application to Image Compressed Sensing

摘要：

GPSR-BB C Gradient Projection for Sparse Reconstruction) algorithm is a popular CS (compressed sensing) reconstruction method.It performs well for questions which have sparse solution. This approach is originally developed in the context of unconstrained minimization of a smooth nonlinear function F,and it uses the search direction of the Quasi-Newton method.So its shortcomings is the same as the Quasi-Newton method.For some reasons,the Hessen matrix of F cant be computed directly,it leads to a performance loss of the algorithm.Based on GPSR-BB approach,a new gradient projection methods called CGSR-FR (Conjugate Gradient for Sparse Reconstruction) is proposed in this paper.Simulation experiments show that CGSR-FR approache perform better than GPSR-BB approache in image compression sampling.

关键词： Conjugate gradient Compressed sensing Natural image Reconstruction SAR image

作者: Fang Liu Hu Wang Hongxia Hao

作者单位: The School of Computer Science and Technology,Xidian University Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University.Xian 710071,China

会议类型: 国际会议

会议名称: 2009 2nd Asian-Pacific Conference on Synthetic Aperture Radar(第二届亚太合成孔径雷达会议)

会议地点: 西安

会议语种:英文

页码: 322-325

在线出版日期: 2009-10-26（万方平台首次上网日期，不代表论文的发表时间）