Fuzzy Techniques for Image Enhancement - Veluchamy, Magudeeswaran
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Fuzzy image processing is a collection of different fuzzy approaches to image processing that can understand, represent, and process the image. It has three main stages, namely, image fuzzification, modification of membership function values, and de-fuzzification. Fuzzy image enhancement is based on gray level mapping into membership function. The aim is to generate an image of higher contrast than the original image by giving a larger weight to the gray levels that are closer to the mean gray level of the image that are farther from the mean or median.

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Produktbeschreibung
Fuzzy image processing is a collection of different fuzzy approaches to image processing that can understand, represent, and process the image. It has three main stages, namely, image fuzzification, modification of membership function values, and de-fuzzification. Fuzzy image enhancement is based on gray level mapping into membership function. The aim is to generate an image of higher contrast than the original image by giving a larger weight to the gray levels that are closer to the mean gray level of the image that are farther from the mean or median.
Autorenporträt
V. Magudeeswaran received the PhD and ME degrees from Anna University, in 2014 and 2007, respectively. He is an Asst.Professor of Electronics and Communication Engineering Department, PSNA College of Engineering and Technology, Dindigul, India. His research interests include computer vision, image and video processing.