Processing of images plays a vital role in many fields such as medical and scientific applications. During the transmission of images, effect of noise plays a key role. A fuzzy filter is presented for additive noise removal from color images. During the process of noise removal, some of the edges may be disappeared. This paper presents two independent fuzzy based edge linking algorithms which are capable of finding a set of edge points in an image and linking these edge points by thresholding. The first algorithm includes a set of 16 fuzzy templates, representing the edge profiles of different types. The second algorithm relies on the image gradient to locate breaks in uniform regions and is based on fuzzy if-then rules. Performance evaluation of these algorithms is known by calculating peak signal to noise ratio (PSNR).
Most of images like medical images, satellite images and even real life photographs may suffer from poor contrast due to the inadequate or insufficient lighting during image acquiring. So there is a necessity of contrast enhancement of images. In this paper three enhancement techniques namely fuzzy rule based contrast enhancement, contrast enhancement using intensification (INT) operator, and contrast enhancement using fuzzy expected value (FEV) are presented for the low contrast grayscale images. Comparative analysis of these enhancement techniques is carried out by means of index of fuzziness (IOF) and processing time.
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