Image filtering is a technique to preserve important signal elements such as edges, smoothing the details of the image to make images appear clear and sharpener. Among all the non linear concepts to suppress Gaussian noise,the fuzzy logic based approaches are important as they are cabable of reasoning with vague and uncertain informations. In this study, we present a new method for the noise reduction of images contaminated with Gaussian noise by using fuzzy image filter with the help of fuzzy rules which make use of membership functions. In this article, fuzzy derivative concept is also applied to perform fuzzy smoothing. This method provides better input for further image processing techniques and also it increases the contrast of the images, fine details and sharpening the edges as well. In this study, comparison is also made with the existing noise reduction methods by numerical measures and visual inspection.
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A New Concept of Reduction of Gaussian Noise in Images Based on Fuzzy Logic
Semantic Scholar · Computer Science · 2013
Abstract
Image filtering is a technique to preserve important signal elements such as edges, smoothing the details of the image to make images appear clear and sharpener. Among all the non linear concepts to suppress Gaussian noise,the fuzzy logic based approaches are important as they are cabable of reasoning with vague and uncertain informations. In this study, we present a new method for the noise reduction of images contaminated with Gaussian noise by using fuzzy image filter with the help of fuzzy rules which make use of membership functions. In this article, fuzzy derivative concept is also applied to perform fuzzy smoothing. This method provides better input for further image processing techniques and also it increases the contrast of the images, fine details and sharpening the edges as well. In this study, comparison is also made with the existing noise reduction methods by numerical measures and visual inspection.