Adaptive smoothness constraint image multilevel fuzzy enhancement algorithm
For the problems of poor enhancement effect and long time consuming of the traditional algorithm, an adaptive smoothness constraint image multilevel fuzzy enhancement algorithm based on secondary color-to-grayscale conversion is proposed. By using fuzzy set theory and generalized fuzzy set theory, a...
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Penerbit Universiti Kebangsaan Malaysia
2019
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my-ukm.journal.144672020-04-21T02:24:04Z http://journalarticle.ukm.my/14467/ Adaptive smoothness constraint image multilevel fuzzy enhancement algorithm Xi, Chu Zhou, Zhixiang Yang, Chaoshan Xiang, Xiaoju For the problems of poor enhancement effect and long time consuming of the traditional algorithm, an adaptive smoothness constraint image multilevel fuzzy enhancement algorithm based on secondary color-to-grayscale conversion is proposed. By using fuzzy set theory and generalized fuzzy set theory, a new linear generalized fuzzy operator transformation is carried out to obtain a new linear generalized fuzzy operator. By using linear generalized membership transformation and inverse transformation, secondary color-to-grayscale conversion of adaptive smoothness constraint image is performed. Combined with generalized fuzzy operator, the region contrast fuzzy enhancement of adaptive smoothness constraint image is realized, and image multilevel fuzzy enhancement is realized. Experimental results show that the fuzzy degree of the image is reduced by the improved algorithm, and the clarity of the adaptive smoothness constraint image is improved effectively. The time consuming is short, and it has some advantages. Penerbit Universiti Kebangsaan Malaysia 2019-12 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/14467/1/19%20Xi%20Chu.pdf Xi, Chu and Zhou, Zhixiang and Yang, Chaoshan and Xiang, Xiaoju (2019) Adaptive smoothness constraint image multilevel fuzzy enhancement algorithm. Sains Malaysiana, 48 (12). pp. 2777-2785. ISSN 0126-6039 http://www.ukm.my/jsm/malay_journals/jilid48bil12_2019/KandunganJilid48Bil12_2019.html |
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For the problems of poor enhancement effect and long time consuming of the traditional algorithm, an adaptive smoothness constraint image multilevel fuzzy enhancement algorithm based on secondary color-to-grayscale conversion is proposed. By using fuzzy set theory and generalized fuzzy set theory, a new linear generalized fuzzy operator transformation is carried out to obtain a new linear generalized fuzzy operator. By using linear generalized membership transformation and inverse transformation, secondary color-to-grayscale conversion of adaptive smoothness constraint image is performed. Combined with generalized fuzzy operator, the region contrast fuzzy enhancement of adaptive smoothness constraint image is realized, and image multilevel fuzzy enhancement is realized. Experimental results show that the fuzzy degree of the image is reduced by the improved algorithm, and the clarity of the adaptive smoothness constraint image is improved effectively. The time consuming is short, and it has some advantages. |
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Article |
author |
Xi, Chu Zhou, Zhixiang Yang, Chaoshan Xiang, Xiaoju |
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Xi, Chu Zhou, Zhixiang Yang, Chaoshan Xiang, Xiaoju Adaptive smoothness constraint image multilevel fuzzy enhancement algorithm |
author_facet |
Xi, Chu Zhou, Zhixiang Yang, Chaoshan Xiang, Xiaoju |
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Xi, Chu |
title |
Adaptive smoothness constraint image multilevel fuzzy enhancement algorithm |
title_short |
Adaptive smoothness constraint image multilevel fuzzy enhancement algorithm |
title_full |
Adaptive smoothness constraint image multilevel fuzzy enhancement algorithm |
title_fullStr |
Adaptive smoothness constraint image multilevel fuzzy enhancement algorithm |
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Adaptive smoothness constraint image multilevel fuzzy enhancement algorithm |
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adaptive smoothness constraint image multilevel fuzzy enhancement algorithm |
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Penerbit Universiti Kebangsaan Malaysia |
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2019 |
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http://journalarticle.ukm.my/14467/1/19%20Xi%20Chu.pdf http://journalarticle.ukm.my/14467/ http://www.ukm.my/jsm/malay_journals/jilid48bil12_2019/KandunganJilid48Bil12_2019.html |
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