湖南大学学报（自然科学版）2017，Vol.44Issue(2)：129-136,8.DOI:10.16339/j.cnki.hdxbzkb.2017.02.019
基于小波变换的图像零树压缩感知方法
Image Zerotree Compressed Sensing Based on Wavelet Transform
摘要
Abstract
The basic principle of Compressed Sensing (CS) theory is that if a signal is sparse, CS promises to deliver a full recovery of this signal with high probability from far fewer measurements than the original signal.Unfortunately, image signals usually are not sparse, and thus it is difficult to obtain high compression performance for image compressed sensing.This paper proposed a simple and efficient zerotree compressed sensing method for images.In the proposed scheme, the classical zerotree coding is integrated into the process of measure to encode the precise locations of significant elements, which is used to restore the original image by the proposed pursuit reconstruction algorithm to improve the quality of the reconstructed image.The experimental results show that, compared with the existing matching pursuit algorithms and Embedded Zerotree Wavelet (EZW) coding algorithm, the proposed algorithm achieves much higher compression ratio and better image quality.关键词
小波变换/图像处理/压缩感知/编码Key words
wavelet transform/image processing/compressed sensing/encoding分类
信息技术与安全科学引用本文复制引用
周四望,刘龙康..基于小波变换的图像零树压缩感知方法[J].湖南大学学报（自然科学版）,2017,44(2):129-136,8.基金项目
国家自然科学基金资助项目(61472131), National Natural Science Foundation of China (61472131) （61472131）
湖南省自然科学基金资助项目(14JJ2051), Natural Science Foundation of Hunan Province of China(14JJ2051) （14JJ2051）
