电子学报2016，Vol.44Issue(3)：613-619,7.DOI:10.3969/j.issn.0372-2112.2016.03.018
融合解析模型和综合模型的压缩感知算法
Compressed Sensing Algorithm Fused the Cosparse Analysis Model and the Synthesis Sparse Model
摘要
Abstract
How to improve the reconstructed image quality using more prior knowledge of the image is still a crucial issue of compressed sensing.In this paper,we combine the synthesis sparse model and the cosparse analysis model proposed in recent years,and propose a novel reconstruction algorithm based on the sparsity of the image over a synthesis dictionary and an analysis dictionary.Moreover,alternating direction method of multipliers ( ADMM) is exploited to solve the corre-sponding complicated optimization problem.To further improve the performance,the sparsity of patches in any position of the image is utilized by the proposed algorithm.The experimental results show that our algorithm can effectively improve the quality of image reconstruction.关键词
压缩感知/稀疏表示/Cosparse解析模型/图像重构Key words
compressed sensing/sparse representation/cosparse analysis model/image reconstruction分类
信息技术与安全科学引用本文复制引用
练秋生,韩敏,石保顺,陈书贞..融合解析模型和综合模型的压缩感知算法[J].电子学报,2016,44(3):613-619,7.基金项目
国家自然科学基金（No．61071200，No．61471313）；河北省自然科学基金 （）
