Removal of Salt-and-Pepper Noise Using Gain Factors Adapted by Noise-Free Pixel Number and Pixel Variation

[[abstract]]A digital image would be corrupted by impulse noise at the time of capturing or transmission, causing the quality of the image to be deteriorated. Noise interference is disadvantageous for further process on the noise-corrupted image. How to effectively remove this impulse noise for a noise-corrupted image is an important research task. In this thesis, we propose a gain factor adapted by noise-free pixel number and pixel variation for the removal of salt-and-pepper noise, enabling the quality of the image to be improved. Initially, a sliding window with the size of 3x3 is employed to analyze the pixels with an extreme value of gray level (255 or 0 for an 8-bit gray-level image). All pixels with non-extreme value of gray level are sorted in an ascending order and are grouped according to the gray-level variation of pixels. If the gray-level variation of pixels between adjacent two sorted pixels varies seriously, a new group is created. Hence, the distribution ratio and median value of each group are computed to determine the values of the gain factors. They are multiplied with the median value of each group to obtain a weighted value which is employed to replace the center pixel with extreme value of gray level, enabling noise-corrupted pixels to be reconstructed. Experimental results show that the proposed approach can effectively remove salt-and-pepper noise from a corrupted image for various noise corruption densities (from 10% to 90%); meanwhile, the denoised image is not blurred