Image Restoration in Noisy free images using fuzzy based median filtering and adaptive Particle Swarm Optimization - Richardson-Lucy algorithm

Abstract

In this paper, we have proposed adaptive methods for image restoration in which the input images are affected by noise which is removed by fuzzy based median filter (FMF). The noise removed images from the FMF is appears to be so there is a need to restore the images with high quality. To restore the images an APSO (Adaptive particle swarm optimization) based Richardson-Lucy (R-L) algorithm is utilized. By both FMF and APSO-RL methods the denoising and restoration of the image is performed efficiently. The performance of the image denoising and restoration technique is evaluated by comparing the result of proposed technique with the existing denoising filter and GA, PSO methods. The comparison result shows a high-quality denoising and restoration ratio for the noisy images than the existing methods, in terms of peak signal-to-noise ratio (PSNR) and second-derivative-like measure of enhancement (SDME).