Image Denoising and Deblurring Using Non-Local Means Algorithm in Monochrome Images
N. Hemalatha · 2014
ABSTRACT – Image deblurring and denoising are the fundamental problems generally arise in the field of image processing with several applications. This paper presents both areas of image restoration. Image deblurring and denoising methods are most commonly designed for removal of both impulsive noise and Gaussian noise. Impulsive noise is a most common noise which affects the image quality during image acquisition, transmission, reception or storage and retrieval process in the area of image denoising. Impulsive noise can be categories into two i.e., Salt and Pepper Noise and Random Valued Impulsive Noise. Image deblurring methods are most commonly designed for Gaussian noise. The proposed work concentrates on removal of both Impulsive noise and Gaussian noise from images. Removal of impulsive noise is carried out using a non-linear filter that involves two phases, i.e. detecting the noise and also followed by filtering. Hence we proposed an efficient filter method for suppressing the noise in an image. The numerical results will confirm that proposed methods yields the better performance, in the terms of PSNR (Peak Signal to