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Image enhancement algorithm using adaptive fractional differential mask technique
Author(s) -
Xuefeng Zhang,
Yan Hui
Publication year - 2019
Publication title -
mathematical foundations of computing
Language(s) - English
Resource type - Journals
ISSN - 2577-8838
DOI - 10.3934/mfc.2019022
Subject(s) - image segmentation , artificial intelligence , image (mathematics) , otsu's method , computer vision , mathematics , image enhancement , algorithm , pattern recognition (psychology) , entropy (arrow of time) , image texture , image quality , computer science , physics , quantum mechanics
This paper addresses a novel adaptive fractional order image enhancement method. Firstly, an image segmentation algorithm is proposed, it combines Otsu algorithm and rough entropy to segment image accurately into the objet and the background. On the basis of image segmentation and the knowledge of fractional order differential, an image enhancement model is established. The rough characteristics of each average gray value are obtained by image segmentation method, through these features, we can determine the optimal fractional order of image enhancement. Then image will be enhanced using fractional order differential mask, from which fractional order is obtained adaptively. Several images are used for experiments, the proposed model is compared with other models, and the results of comparison exhibit the superiority of our algorithm in terms of image quality measures.

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