DocumentCode :
626232
Title :
Soft Switching Technique for Impulsive Noise Removal in Color Images
Author :
Smolka, Bogdan
Author_Institution :
Dept. of Autom. Control, Silesian Univ. of Technol., Gliwice, Poland
fYear :
2013
fDate :
5-7 June 2013
Firstpage :
222
Lastpage :
227
Abstract :
In this paper a novel, fast soft switching filtering technique intended for impulsive noise removal in color images is presented. The impulsive noise detection algorithm is based on the concept of trimmed cumulated distances, which are assigned to the central pixel of a sliding filtering window. The trimmed sum of distances serves as an indicator of the strength of impulses injected to the image by the impulsive noise process and the restored pixel is obtained as a weighted mean of the processed pixel and the sharpening vector median filter output. Extensive experiments, performed on a set of color test images, proved that the proposed filter is superior to the state-of-the-art impulsive noise reduction algorithms. The new noise filtering design, due to its simple structure and very low computational complexity, can be applied in various applications in which the detail preserving impulsive noise reduction is required.
Keywords :
computational complexity; image colour analysis; image denoising; image restoration; median filters; central pixel; color test images; computational complexity; fast soft switching filtering technique; impulsive noise detection algorithm; impulsive noise removal; pixel restoration; sharpening vector median filter output; sliding filtering window; trimmed cumulated distances; weighted mean; Color; Image color analysis; Noise reduction; PSNR; Soft switching; Vectors; image enhancement; impulsive noise removal;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence, Communication Systems and Networks (CICSyN), 2013 Fifth International Conference on
Conference_Location :
Madrid
Print_ISBN :
978-1-4799-0587-4
Type :
conf
DOI :
10.1109/CICSYN.2013.22
Filename :
6571369
Link To Document :
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