Image Enhancement Based on Rough Set and Fractional Order Differentiator

In the paper, an image enhancement algorithm based on a rough set and fractional order differentiator is proposed. By combining the rough set theory with a Gaussian mixture model, a new image segmentation algorithm with higher immunity is obtained. This image segmentation algorithm can obtain more i...

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Bibliographic Details
Published inFractal and fractional Vol. 6; no. 4; p. 214
Main Authors Zhang, Xuefeng, Dai, Lewen
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.04.2022
Subjects
Algorithms
Approximation
Clustering
Differentiators
Fourier transform
Fourier transforms
fractional order differentiator
Fuzzy sets
Gaussian mixture model
Image enhancement
Image segmentation
Mathematical functions
Numerical analysis
Probabilistic models
rough set theory
Set theory
Signal processing
Variables
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Summary:In the paper, an image enhancement algorithm based on a rough set and fractional order differentiator is proposed. By combining the rough set theory with a Gaussian mixture model, a new image segmentation algorithm with higher immunity is obtained. This image segmentation algorithm can obtain more image layers with concentrating information and preserve more image details than traditional algorithms. After preprocessing, the segmentation layers will be enhanced by a new adaptive fractional order differential mask in the Fourier domain. Experimental results and numerical analysis have verified the effectiveness of the proposed algorithm.
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ISSN:2504-3110
2504-3110
DOI:10.3390/fractalfract6040214