计算机工程2017，Vol.43Issue(9)：281-287,7.DOI:10.3969/j.issn.1000-3428.2017.09.049
基于分类冗余字典稀疏表示的图像压缩方法
Image Compression Method Based on Sparse Representation of Classified Redundant Dictionary
摘要
Abstract
When images are decompressed at high compression rate,the compression standard JPEG and JPEG 2000 will cause distortion.The use of redundant dictionary for sparse representation can obtain better quality of image decompression at high compression rates,but the single redundant dictionary cannot fully represent the structure of image.In view of the above problems,an image compression method based on sparse representation of classified redundant dictionary is proposed.It uses Kernel Singular Value Decomposition (KSVD) algorithm to train smoothing and detailed redundant dictionaries respectively,and uses improved Orthogonal Matching Pursuit(OMP) algorithm to represent images sparsely according to the relationship between the correlation coefficient of dictionary atoms and image signals and the representation error,so that smoothing representation coefficients and detailed representation coefficients without much lower values are respectively obtained.Finally,these coefficients and their corresponding indexes of dictionary atoms are quantified coded to compress images.Experimental results show that the proposed method can get decompressed images with better visual effect compared with JPEG,JPEG 2000 and the method based on single redundant dictionary at the high compression ratio.关键词
图像压缩/相关系数/分类冗余字典/稀疏系数/正交匹配追踪Key words
image compression/correlation coefficient/classified redundant dictionary/sparse coefficient/Orthogonal Matching Pursuit (OMP)分类
信息技术与安全科学引用本文复制引用
王科平,杨赞亚,恩德..基于分类冗余字典稀疏表示的图像压缩方法[J].计算机工程,2017,43(9):281-287,7.基金项目
国家自然科学基金青年基金(61405055) （61405055）
河南省教育厅科学技术研究重点项目(15A510025) （15A510025）
河南理工大学博士基金(B2012-0670). （B2012-0670）
