文献类型：期刊文献

英文题名：A Two-Stage Algorithm for the Detection and Removal of Random-Valued Impulse Noise Based on Local Similarity

作者：Lin, Cong[1,2];Li, Yuchun[1];Feng, Siling[1];Huang, Mengxing[1]

机构：[1]Hainan Univ, Coll Informat & Commun Engn, Haikou 570228, Hainan, Peoples R China;[2]Guangdong Ocean Univ, Coll Elect & Informat Engn, Zhanjiang 524000, Peoples R China

年份：2020

卷号：8

起止页码：222001

外文期刊名：IEEE ACCESS

收录：SCI-EXPANDED(收录号：WOS:000603850400001)、、EI(收录号：20210109707847)、Scopus(收录号：2-s2.0-85098324509)、WOS

基金：This work was supported in part by the National Key Research and Development Program of China under Grant 2018YFB1404400.

语种：英文

外文关键词：Noise reduction; Image restoration; Image edge detection; Noise measurement; Gray-scale; Detectors; Image denoising; Image denoising; random-valued impulse noise; local similarity; bilateral filter

外文摘要：A two-stage denoising algorithm based on local similarity is proposed to process lowly and moderate corrupted images with random-valued impulse noise in this paper. In the noise detection stage, the pixel to be detected is centered and the local similarity between the pixel and each pixel in its neighborhood is calculated, which can be used as the probability that the pixel is noise. By obtaining the local similarity of each pixel in the image and setting an appropriate threshold, the noise pixels and clean pixels in the damaged image can be detected. In the image restoration stage, an improved bilateral filter based on local similarity and geometric distance is designed. The pixel detected as noise in the first stage is filtered and the new intensity value is the weighted average of all pixel intensities in its neighborhood. A large number of experiments have been conducted on different test images and the results show that compared with the mainstream denoising algorithms, the proposed method can detect and filter out the random-value impulse noise in the image more effectively and faster, while better retaining the edges and other details of the image.