Image enhancement based on fractional calculus and genetic algorithm

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Abstract

Image enhancement is an interesting topic in the image processing area. In this work, image enhancement with fractional-order derivative and genetic algorithm is proposed. Fractional-order derivative possesses a non-local property, which is helpful to find the fine edges of the image. In this paper, firstly, fractional-order partial differences are computed in forward x-direction, backward x-direction, forward y-direction, and backward y-direction. These differences are represented based on discrete Fourier transform (DFT). Finally, genetic algorithm (GA) is applied for the fractional-order selection to get optimum results and the fractional-order is chosen in the range from 0 to 1. The experimental results give the superiority of the proposed algorithm than the traditional methods.

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Sridevi, G., & Srinivas Kumar, S. (2019). Image enhancement based on fractional calculus and genetic algorithm. In Lecture Notes on Data Engineering and Communications Technologies (Vol. 28, pp. 197–206). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-13-6459-4_20

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