计算机技术与发展Issue(1)：47-50,4.DOI:10.3969/j.jssn.1673-629X.2013.01.012
基于灰度纹理信息的图像压缩感知编码与重构
Coding and Reconstruction of Image Compressed Sensing Based on Gray-scale Texture Information
摘要
Abstract
It introduced the CS ( Compressed Sensing) theory and proposed a novel gray-scale-texture compressive sampling method based on DCT coefficients distribution characteristics for image signals. This method extracts the energy of DCT alternating current coeffi-cient in image block to use for weighted correction in measurement process,makes full use of alternating current component coefficient of representing image detail texture information to allocate the measuring dimension based on image contour texture detail information,and ultimately realizes the distinguishing compression sampling for different image blocks. Comparison results with the similar work demon-strate that the proposed compressive sampling method could not only efficiently reduce the computational complexity,but also considera-bly decrease measurement rate and/ or enhance the recovery image quality in both PSNR and subjective visual quality.关键词
压缩感知/DCT 稀疏投影/交流分量/灰度纹理信息Key words
compressive sensing/DCT sparse decomposition/AC coefficients/gray-scale texture information分类
信息技术与安全科学引用本文复制引用
张晓咏,熊承义,胡开云,时翔..基于灰度纹理信息的图像压缩感知编码与重构[J].计算机技术与发展,2013,(1):47-50,4.基金项目
国家自然科学基金资助项目(60972081) （60972081）
湖北自然科学基金(2009CDA139,2010CDZ022) （2009CDA139,2010CDZ022）
