A study on genetic expression programming-based approach for impulse noise reduction in images. Issue 3 (March 2016)

• Record Type: Journal Article
• Authors: Bhadouria, Vivek; Ghoshal, Dibyendu
• Is Part Of: Signal, image and video processing. Volume 10:Issue 3(2016)
• Page Start: 575
• Page End: 584
• Publication Date: 2016-03
• Subjects: Filtering -- Genetic expression programming -- Impulse detection -- Impulse noise -- Noise reduction; Signal processing -- Digital techniques -- Periodicals; Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; 621.3822
• DOI: 10.1007/s11760-015-0780-6
• Languages: English
• ISSNs: 1863-1703

Abstract

Abstract Existing impulse noise reduction techniques perform well at low noise densities; however, their performance drops sharply at higher noise densities. In this paper, we propose a two-stage scheme to surmount this problem. In the proposed approach, first stage consists of impulse detection unit followed by the filtering operation in the second stage. We have employed a genetic expression programming-based classifier for the detection of impulse noise-corrupted pixels. To reduce the blurring effect caused due to filtering operation on the noise-free pixels, we filter the detected noisy pixels only by using a modified median filter. Better peak signal-to-noise ratio, structural similarity index measure, and visual output imply the efficacy of the proposed scheme for noise reduction at higher noise densities.