Super-Resolution using Regularized Orthogonal Matching Pursuit based on Compressed Sensing Theory in the Wavelet Domain

被引:0
|
作者
Li, Tingting [1 ]
机构
[1] Chongqing Univ, Coll Math & Phys, Chongqing 400044, Peoples R China
来源
IEEE INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN ROBOTICS AND AUTOMATION | 2009年
关键词
SIGNAL 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
We proposed a compressed sensing Super Resolution algorithm based on wavelet. The proposed algorithm performs well with a smaller quantity of training image patches and outputs images with satisfactory subjective quality. It is tested on classical images commonly adopted by Super Resolution researchers with both generic and specialized training sets for comparison with other popular commercial software and state-of-the-art methods. Experiments demonstrate that, the proposed algorithm is competitive among contemporary Super Resolution methods.
引用
收藏
页码:234 / 239
页数:6
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