Empirical Evaluation of Particle Filtering and Non Local Mean Method Image Reconstruction Techniques

Abstract

Image reconstruction is the process of manipulating an image to increase the amount of information perceived by a human eye. In this paper most popular filtering techniques have taken i.e., Particle filtering and Non Local Mean method. The particle filtering technique will give statistical behavior of the image. The most appropriate window or neighborhood shape and size to estimate the image intensity in a given position. One attempt is to do perform filtering by selecting the neighboring pixels in a random fashion but without taking image structure into account. The Original NL Mean method replaces a noisy pixel by the weighted average of pixels with related surrounding neighbourhoods.Inorder to accelerate the algorithm; the filters are used to eliminate unrelated neighborhoods from the weighted average. The results of techniques Particle Filters and Non Local Mean methods are compared by using two parameters such as PSNR and MSE values for the reconstructed images. Particle filter method provides a better result when compare to Nonlocal mean method.