Pixon Based Image Denoising Scheme by Preserving Exact Edge Locations

Abstract

Denoising of an image is an essential step in many image processing applications. In any image de-noising algorithm, it is a major concern to keep interesting structures of the image like abrupt changes in image intensity values (edges). In this paper an efficient algorithm for image de-noising is proposed that obtains integrated and consecutive original image from noisy image using diffusion equations in pixon domain. The process mainly consists of two steps. In first step, the pixons for noisy image are obtained by using K-means clustering process and next step includes applying diffusion equations on the pixonal model of the image to obtain new intensity values for the restored image. The process has been applied on a variety of standard images and the objective fidelity has been compared with existing algorithms. The experimental results show that the proposed algorithm has a better performance by preserving edge details compared in terms of Figure of Merit and improved Peak-to-Signal–Noise-Ratio value. The proposed method brings out a denoising technique which preserves edge details.