Fuzzy Logic Based Contrast Enhancement
A novel improved fuzzy logic based image enhancement method using local information from the sub-images has been proposed in this work. The proposed methodology enhances only the V component of HSV colour space model of the sub-images, which carries the achromatic information of the image, retaining the hue and saturation components. For effectively extracting the local information, the number of sub-images has been optimized using bacterial foraging optimization algorithm. The enhancement process employs the fuzzy logic which computes the enhanced intensity values of the sub-image pixels depending on the average intensity value of the sub-images and a contrast intensification parameter. The performance of the enhancement
process has been judged in terms of performance measures like Tenengrad and contrast improvement index. The combination of all the enhanced sub-images shows 35-45% improvement over the fuzzy based and histogram equalization based other techniques in the literature.
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