Switching impulse noise filter based on Laplacian convolution and pixels grouping for color images

Switching impulse noise filter based on Laplacian convolution and pixels grouping for color images This paper presents a new switching filter consisting of three steps to restore color images corrupted by impulse noise. Firstly, Laplacian convolution is performed on pixels in four directions to mark the pixels which are radically different in value from neighboring pixels as noise candidates. Secondly, those missed neighboring pixels involved in the step of pixels grouping decrease the occurrence of false detection. Pixels in the observation window are separated into noisy pixels and normal pixels with a dividing threshold, whose value is assigned according to a noise density estimator. Finally, a modified arithmetic mean filter is applied to restore the polluted image. Extensive experiments show that the proposed method achieves better performance than comparative methods in terms of peak-signal-to-noise ratio and structural similarity. The proposed method can effectively remove impulse noise in which noise density is varying from 10 to 80%. Keywords Impulse noise removal · Laplacian convolution · Pixels grouping · Arithmetic mean filter 1 Introduction takes into account the relationship of the red, green and blue channels by utilizing Euclidean distance and is more suit- Color images are often corrupted by impulse noise. It able for color images. Except for the distance measurement, brings difficulties to http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png "Signal, Image and Video Processing" Springer Journals

Switching impulse noise filter based on Laplacian convolution and pixels grouping for color images

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Publisher
Springer London
Copyright
Copyright © 2018 by Springer-Verlag London Ltd., part of Springer Nature
Subject
Computer Science; Image Processing and Computer Vision; Signal,Image and Speech Processing; Computer Imaging, Vision, Pattern Recognition and Graphics; Multimedia Information Systems
ISSN
1863-1703
eISSN
1863-1711
D.O.I.
10.1007/s11760-018-1308-7
Publisher site
See Article on Publisher Site

Abstract

This paper presents a new switching filter consisting of three steps to restore color images corrupted by impulse noise. Firstly, Laplacian convolution is performed on pixels in four directions to mark the pixels which are radically different in value from neighboring pixels as noise candidates. Secondly, those missed neighboring pixels involved in the step of pixels grouping decrease the occurrence of false detection. Pixels in the observation window are separated into noisy pixels and normal pixels with a dividing threshold, whose value is assigned according to a noise density estimator. Finally, a modified arithmetic mean filter is applied to restore the polluted image. Extensive experiments show that the proposed method achieves better performance than comparative methods in terms of peak-signal-to-noise ratio and structural similarity. The proposed method can effectively remove impulse noise in which noise density is varying from 10 to 80%. Keywords Impulse noise removal · Laplacian convolution · Pixels grouping · Arithmetic mean filter 1 Introduction takes into account the relationship of the red, green and blue channels by utilizing Euclidean distance and is more suit- Color images are often corrupted by impulse noise. It able for color images. Except for the distance measurement, brings difficulties to

Journal

"Signal, Image and Video Processing"Springer Journals

Published: May 30, 2018

References

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