电波科学学报2011，Vol.26Issue(3)：533-538,6.
基于自适应稀疏表示的被动毫米波图像恢复
Passive millimeter wave image restoration based on adaptive sparse representation
摘要
Abstract
A novel passive millimeter wave image restoration method is proposed, which aims to overcome the shortcoming that Fourier and wavelet domain regulari- zation methods can not de-noise effectively and maintain target features simultane- ously. The new method takes advantage of sparse representation＇s merit of repre- senting signals flexibly. It learns from the millimeter wave image after inverse filte- ring by using K-clustering with singular value decomposition （K-SVD） algorithm to obtain basis functions adaptively for image restoration. Comparing with Fourier and wavelet domain regularization methods, the proposed method employs an adaptive method. So it can maintain target features better and de-noise more effectively, which leads to better image restoration. When the method was used in the restora- tion of simulated passive millimeter image, good result has been obtained. There- fore, it is an effective passive millimeter imaging method.关键词
自适应稀疏表示/被动毫米波/图像恢复/K—SVD/去噪Key words
adaptive sparse representation/passive millimeter wave/image restora- tion/K-SVD/denoise分类
信息技术与安全科学引用本文复制引用
成萍,赵家群,张春杰,司锡才..基于自适应稀疏表示的被动毫米波图像恢复[J].电波科学学报,2011,26(3):533-538,6.基金项目
国防基础科研基金 （）
中央高校基本科研业务费专项资金 （）
中国博士后基金 （）
黑龙江省博士后基金 （）
