A Fuzzy Rule-based Preprocessing Classifier for Removal of Impulse Noises in Digital Images
碩士 === 國立宜蘭大學 === 電子工程學系碩士班 === 102 === The research of image restoration and reconstruction existed for a long time, many kinds of filters algorithms have been proposed for removing impulse noise from digital images in the past few decades. In this study, a fuzzy preprocessing classifier is used to...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2014
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| Online Access: | http://ndltd.ncl.edu.tw/handle/fv3k8t |
| Summary: | 碩士 === 國立宜蘭大學 === 電子工程學系碩士班 === 102 === The research of image restoration and reconstruction existed for a long time, many kinds of filters algorithms have been proposed for removing impulse noise from digital images in the past few decades. In this study, a fuzzy preprocessing classifier is used to categorize five distribution types which were identified as noise by noise detection. This method can extract useful local information from the corrupted image which is supported to the filter processing and results more image details to preserve. The fuzzy preprocessing classifier goes through four-phase detection procedures to determine the condition of central pixel of local image window by using the similarity between neighboring pixels. A filters’ system is set up by our proposed fuzzy preprocessing classifier with several effective filters to verify its performance. Simulations results are compared with other individual filters by objectively numerical measured and subjectively visual inspection indicate that our method performs significantly better in terms of noise suppression and detail preservation than others. The proposed method in this paper has great superiority over the earlier methods and undoubtedly will provide solid basis for subsequent filtering stage.
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