Fuzzy Based Median Filter for Gray-scale Images

Digital image processing is a subset of the electronic domain wherein the image is converted to an array of small integers, called pixels, representing a physical quantity such as scene radiance, stored in a digital memory, and processed by computer or other digital hardware. The application of median filter has been investigated. As an advanced method compared with standard median filtering, the Adaptive Median Filter performs spatial processing to preserve detail and smooth non-impulsive noise. Fuzzy logic represents a good mathematical framework to deal with uncertainty of information. Fuzzy image processing [4] is the collection of all approaches that understand, represent and process the images, their segments and features as fuzzy sets.In this paper, we propose a Fuzzy based median filter, to achieve improved filtering performance in terms of effectiveness in removing salt-and-pepper noise while preserving image details and smooth non-impulsive noise. Proposed method work in two steps, in first step we detect noisy pixels using fuzzy reasoning with lowest uncertainty, and in second step we replace noisy pixels with a adaptive noise filter, our this filter is combined with human knowledge for select best replacement. Experimental results show that our proposed method outperforms the standard median based techniques in term of PSNR values.