Open AccessAdaptive Technique for Salt and Pepper Noise Removal through Functional Link Artificial Neural Network
Author(s) -
Sunita Sarangi,
Suchitra Sarangi
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.b3959.129219
Subject(s) - salt and pepper noise , pixel , noise (video) , artificial neural network , computer science , artificial intelligence , median filter , filter (signal processing) , pattern recognition (psychology) , image (mathematics) , adaptive filter , computer vision , algorithm , mathematics , image processing
In this paper, an adaptive method for removing salt and pepper noise from images is proposed. A second order difference operator is used to locate the corrupted pixels in images by comparing with a threshold, which is selected adaptively using the image properties. A functional link artificial neural network (FLANN) based method is proposed to set a threshold for each corrupted image for identification of noisy pixels using recursive zero attracting least mean square (RZALMS) as the updating algorithm. Median filter is used to eliminate noise from the detected pixel locations.