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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/38110

Title: Histogram-based fuzzy filter for image restoration
Authors: Jung-Hua Wang
Wen-Jeng Liu
Lian-Da Lin
Contributors: 國立臺灣海洋大學:電機工程學系
Keywords: median filters
fuzzy logic
image restoration
Date: 2002
Issue Date: 2016-08-04T02:09:06Z
Publisher: IEEE Transactions on Systems, Man, and Cybernetics
Abstract: Abstract: In this paper, we present a novel approach to the restoration of noise-corrupted image, which is particularly effective at removing highly impulsive noise while preserving image details. This is accomplished through a fuzzy smoothing filter constructed from a set of fuzzy membership functions for which the initial parameters are derived in accordance with input histogram. A principle of conservation in histogram potential is incorporated with input statistics to adjust the initial parameters so as to minimize the discrepancy between a reference intensity and the output of defuzzification process. Similar to median filters (MF), the proposed filter has the benefits that it is simple and it assumes no a priori knowledge of specific input image, yet it shows superior performance over conventional filters (including MF) for the full range of impulsive noise probability. Unlike in many neuro-fuzzy or fuzzy-neuro filters where random strategy is employed to choose initial membership functions for subsequent lengthy training, the proposed filter can achieve satisfactory performance without any training
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/38110
Appears in Collections:[電機工程學系] 期刊論文

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