吉首大学学报：自然科学版2012，Vol.33Issue(4)：83-86,4.
基于加权L_1最小化的图像小波域压缩感知重构
Weighted Minimization for Compressive Sensing Image Reconstruction in Wavelet Domain
摘要
Abstract
Compressive sensing has received much attention in the signal processing field for it can recon- struct a signal or image from surprisingly few samples. In this paper,the author investigates the wavelet domain image reconstruction problem and proposes a weighted I i minimization algorithm to reconstruct the images. The proposed method utilizes not only the sparsity of signals,but also incorporates the struc- ture information of images in wavelet domain. Hence, compared with the classical compressive sensing al- gorithm, the proposed method has better recoverability. Simulation results show that the proposed meth- od has achieved the same equality image from few samples, which demonstrates the validity of the pro- posed method.关键词
压缩感知/图像重构/小波/基追踪Key words
compressive sensing/image reconstruction/wavelet/basis pursuit分类
信息技术与安全科学引用本文复制引用
张军..基于加权L_1最小化的图像小波域压缩感知重构[J].吉首大学学报：自然科学版,2012,33(4):83-86,4.基金项目
国家自然科学基金资助项目 （）
