Image Denoising Method Based on -Support Vector Regression and Noise Detection

DOI

10.2991/iccia.2012.246How to use a DOI?

Keywords

Salt & pepper noise, -support vector regression, Noise Detection, Block uniformity, Image denoising

Abstract

Aimed at the correlation between noise pixels and neighboring pixels, a new method based on the -support vector regression ( -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 -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 quanti-tative measures.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Changyou Wang
AU  - Zhaolong Gao
PY  - 2014/05
DA  - 2014/05
TI  - Image Denoising Method Based on -Support Vector Regression and Noise Detection
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 1006
EP  - 1009
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.246
DO  - 10.2991/iccia.2012.246
ID  - Wang2014/05
ER  -