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Image enhancement based on fractional directional derivative

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Abstract

This paper introduces the directional derivative to fractional derivative and proposes a new mathematical method, fractional directional derivative (FDD), and gives the corresponding numerical calculation. Compared with the traditional fractional derivative, the coefficients of FDD along the eight directions in the image plane are not the same, which can reflect different fractional change rates along different directions and is benefit to enlarge the differences among the image textures. Experiments show that the capability of nonlinearly enhancing texture details by FDD is more obvious than those by the traditional fractional derivative and integer-order differentiation operators Laplacian, Butterworth high-pass filter.

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Acknowledgments

This work is supported the project of Science and Technology Department of Sichuan Province (No. 2011JY0077), and the project of Chengdu City Economic and Information Technology Commission (No. 201201014).

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Authors and Affiliations

  1. College of Information Science and Technology, Chengdu University, Chengdu, 610106, China

    Chaobang Gao, Chang Liu & Qiang Pu

  2. School of Computer, Sichuan University, Chengdu, 610065, China

    Jiliu Zhou

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  1. Chaobang Gao
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  2. Jiliu Zhou
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  3. Chang Liu
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  4. Qiang Pu
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Correspondence to Chaobang Gao.

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Gao, C., Zhou, J., Liu, C. et al. Image enhancement based on fractional directional derivative. Int. J. Mach. Learn. & Cyber. 6, 35–41 (2015). https://doi.org/10.1007/s13042-014-0247-z

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  • DOI: https://doi.org/10.1007/s13042-014-0247-z

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