计算机技术与发展2017，Vol.27Issue(10)：39-42,4.DOI:10.3969/j.issn.1673-629X.2017.10.009
非局部均值的彩色图像去噪方法改进
Modification on Color Image Denoising Algorithm with Non-local Means
摘要
Abstract
Gaussian weights Euclidean distance between pixel blocks with a high degree of similarity in the neighborhood is calculated to estimate current pixel value in fast non-local means algorithm,which achieves good results in the low-frequency part of the image,but loses partial edge information in the high-frequency part of the image because similarity between pixel blocks cannot be reflected by Gaussian weights Euclidean distance effectively. In order to retain more information in the high-frequency part of the image, a new weighting function is constructed,in which feature similarity color index composed of phase congruency,gradient and chrominance infor-mation is introduced into Gaussian weights Euclidean distance of fast non-local means algorithm and a denoising method is proposed based on it. Similarity between pixel blocks is computed by this new weighting function. Thus the estimated points are acquired with all pixels in three channels of color image filtering with block-by-block and averaged to obtain the entire filtered image. The experimental results show that compared with fast non-local means algorithm,it has improved the PSNR,FSIMC and retained more detail.关键词
非局部均值算法/彩色图像去噪/彩色图像特征相似指数/权重函数Key words
non-local means/color image denoising/color image feature similarity index/weighting function分类
信息技术与安全科学引用本文复制引用
张丽红,焦韶波..非局部均值的彩色图像去噪方法改进[J].计算机技术与发展,2017,27(10):39-42,4.基金项目
山西省科技攻关计划(工业)资助项目(2015031003-1) （工业）
