Support Vector Regression Based Color Image Restoration in YUV Color Space

作     者：黎明 杨杰 苏中义 LI Ming1,2,YANG Jie1,SU Zhong-yi2(1.Institute of Image Processing and Pattern Recognition,Shanghai Jiaotong University,Shanghai 200240,China;2.Department of Electronic Engineering,Shanghai Dianji University,Shanghai 200240,China)

作者机构：Institute of Image Processing and Pattern RecognitionShanghai Jiaotong University Department of Electronic EngineeringShanghai Dianji University 

出 版 物：《Journal of Shanghai Jiaotong university(Science)》 (上海交通大学学报（英文版）)

年 卷 期：2010年第15卷第1期

页      面：31-35页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 080203[工学-机械设计及理论] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：the National Natural Science Foundation of China (No. 60675023) 

主　　题：color image restoration support vector regression (SVR) color space 

摘      要：A support vector regression(SVR) based color image restoration algorithm is *** test color images are firstly mapped into the YUV color space,and then SVR is applied to build up a theoretical model between the degraded images and the original *** comparisons of the proposed algorithm versus traditional filtering algorithms are *** results show that the proposed algorithm has better performance than traditional filtering algorithms and has less computation time than iterative blind deconvolution algorithm.