计算机工程Issue(2)：229-232,4.DOI:10.3969/j.issn.1000-3428.2014.02.049
基于压缩感知的图像重构算法
Image Reconstruction Algorithm Based on Compressed Sensing
摘要
Abstract
There are some problems in the typical gradient projection algorithms in the application of Compressed Sensing(CS), such as the large amount of calculation, the low efficiency of convergence process and excessive dependence on the sparsity of the data matrix. In order to deal with these problems, an efficient recovery algorithm is proposed. This algorithm is based on CS which combines the Quasi-Newton method and the gradient projection method. So it can make full use of the estimating and correcting procedure and the global superlinear convergence of the Quasi-Newton method. By correcting the objective function with the Quasi-Newton method, a more accurate searching direction and fewer iteration can be got. It makes the algorithm perform efficiently with a high convergent reconstruction based on compressed sensing. Experimental results prove that this algorithm shows a good reconstruction and anti-noise performance. Compared with the traditional gradient projection recovery method, the proposed method drops the error rate to make a more stable and convergent reconstruction with fewer iteration.关键词
压缩感知/梯度投影/拟牛顿法/重构/稳定性/收敛性Key words
Compressed Sensing(CS)/gradient projection/Quasi-Newton method/reconstruction/stability/convergence分类
信息技术与安全科学引用本文复制引用
史久根,吴文婷,刘胜..基于压缩感知的图像重构算法[J].计算机工程,2014,(2):229-232,4.基金项目
广东省教育部产学研结合基金资助项目(2009B090300302) （2009B090300302）
