基于奇异值分解的数字图像压缩及重构研究  

Digital Image Compression and Reconstruction Based on Singular Value Decomposition

作　　者：张帅[1] 董亚芬[1] ZHANG Shuai;DONG Ya-fen

机构地区：[1]运城学院物理与电子工程系,山西运城044000

出　　处：《信息技术与信息化》2017年第1期112-115,共4页Information Technology and Informatization

摘　　要：为了解决未压缩的数字图像传输过程中占用网络资源过大的问题,本文利用奇异值分解的方法对数字图像进行压缩重构,达到了简化数据的目的,极大地降低了数字图像传输所占用的资源,同时能够保证重构的图像失真度较小。仿真结果表明,奇异值分解方法能够有效压缩重构图像,且压缩图像时选择的奇异值数量越多,重构图像的质量越好。In order to solve the problem that the network resources are too large in the process of uncompressed digital image transmission,the singular value decomposition(SVD)method is used to compress and reconstruct the digital image.This method achieves the purpose of simplifying the data,greatly reducing the resources occupied by the digital image transmission,and ensuring the reconstructed image distortion is small.The simulation results show that the SVD can effectively compress the reconstructed image.And the more singular values are selected,the better the reconstructed image quality.

关 键 词：奇异值分解 图像压缩 重构图像质量 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]