LOCAL ENHANCED METHODOLGY FOR NOISE FILTERING AND EDGE DETECTION USING FUZZY LOGIC ON 2 DIMENSIONAL IMAGES ,EXTENSION TO N DIMENSION

Abstract

Image processing is any form of information processing for which both the input and output are images, such as photographs or frames of video. Most image processing techniques involve treating the image as a two-dimensional signal and applying standard digital signal processing techniques to it. There are various techniques for processing an image such as linear scaling, optical methods, digital processing, fuzzy techniques. The general idea behind a filter to average a pixel using other pixels from its neighborhood and simultaneously taking care of other features such as edges, blurriness and haziness of the testing images. The main concern of the proposed filter is to distinguish between any variation of the captured digital image due to noise and image structure. The variation can be due to external reasons such as air, climate troubles, remote sensing , water on image structures. The most interesting image enhancement techniques involves edge detection techniques as well as noise removal techniques as loss of edges make the picture blurred or unfocused. However noise smoothing and edge enhancement methods are traditionally most conflicting tasks. In this paper a new fuzzy mechanism is developed for noise reduction of images corrupted by additive noise as well as protecting the edges. The proposed mechanism consists of 3 stages.(1). Define fuzzy sets in the input space to compute fuzzy derivative.(2).To construct if then else rule to perform fuzzy smoothing according to the contribution of surrounding pixel values (3). Define fuzzy sets in the outer space to get maximum noise free and edged image. Experimental results are obtained to show the feasibility of the proposed filter for two dimensional images.