Alternating Minimization Algorithm for Sparse Image Reconstruction

被引：0
|
作者：
Zhu, Yonggui [1 ]
机构：
[1] Commun Univ China, Sch Sci, Beijing 100024, Peoples R China
来源：
2011 INTERNATIONAL CONFERENCE ON COMPUTERS, COMMUNICATIONS, CONTROL AND AUTOMATION (CCCA 2011), VOL II | 2010年
关键词：
Compressed Sensing; Total Variation; Wavelet Transform; Image Reconstruction; RECOVERY;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The alternating minimization algorithm can recover images with blurry and noisy data. In this paper, we apply this algorithm into sparse image reconstruction in compressed sensing. The phantom image is employed to test in the numerical experiments, and the results demonstrate that the alternating minimization method can reconstruct the sparse image from partial radial samples.
引用
收藏
页码：264 / 267
页数：4
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