Image Denoising Method Based on v-Support Vector Regression and Noise Detection
Aimed at the correlation between noise pixels and neighboring pixels,a new method based on the V-support vector regression (V-SVR) is proposed to remove the salt & pepper noise in corrupted images.The new algorithm first takes a decision whether the pixel under test is noise or not by comparing the block uniformity of the 3x3 window with one of the entire image,secondly adjusts adaptively the size of filtering window which is used to determine the training set according to the number of noise points in the window,thirdly determines the decision function that is used to predict the gray value of the noise pixels by means of training set,finally removes the noises in terms of the decision function based on V-SVR.Experimental results clearly indicate that the proposed method has a better filtering effect than the existing methods such as standard mean filter,standard median filter,adaptive median filter by means of visual quality and quantitative measures.
Salt & pepper noise V-support vector regression Noise Detection Block uniformity Image denoising
Changyou Wang Zhaolong Gao Changyou Wang Zhaolong Gao Changyou Wang
College of Computer Science and Technology Chongqing University of Posts and Telecommunications, Cho Key Laboratory of Industrial Internet of Things & Networked Control of Ministry of Education, Chongq College of Mathematics and Physics, Chongqing University of Posts and Telecommunications Chongqing,
国际会议
太原
英文
1006-1009
2012-12-08（万方平台首次上网日期，不代表论文的发表时间）