计算机应用研究2018，Vol.35Issue(3)：934-939,6.DOI:10.3969/j.issn.1001-3695.2018.03.062
基于小波和PCA的自适应颜色空间彩色图像去噪
Color image denoising based on wavelet and PCA in adaptive color space
摘要
Abstract
In color image denoising task,there is a strong correlation between color channels,and the correlation makes the denoised image appear color mutation,which affect the image denoising.In order to solve this problem,this paper put forward a method to reduce the mutual correlation between color channels.Based on the wavelet transform domain coefficient that had aggregation characeristics,the method used PCA to determine principal direction and secondary principal direction of coefficient aggregation,an adaptive linear transform space.After that,it used their directions to determine adaptive color space where color image denoising could be achieved.The experimental results show that,this method is better in view of subjective parameters and objective parameters,which contains the peak signal to noise ratio and sparse feature fidelity.关键词
小波变换/主成分分析/颜色空间/彩色图像去噪Key words
wavelet transform/principal component analysis(PCA)/color space/color image denoising分类
信息技术与安全科学引用本文复制引用
兰小艳,陈莉,贾建,李熠晨..基于小波和PCA的自适应颜色空间彩色图像去噪[J].计算机应用研究,2018,35(3):934-939,6.基金项目
国家自然科学基金资助项目(61379010,61502219) （61379010,61502219）
国家科技支撑计划资助项目(2013BAH49F03) （2013BAH49F03）
中国博士后科学基金资助项目(2015M582697) （2015M582697）
