Abstract
Aiming at the existing problems that the image denoising algorithm based on integer-order partial differential equation could lost part of edge and texture information. This image denoising algorithm based on fractional variational theory was proposed by the theory of fractional calculus and partial differential equation. The denoising model proposed in this paper introduces and implements the numeric computation of the fractional variation partial differential equations by constructing the fractional differential mask operators along eight directions of image. The simulation data prove that the image denoising algorithm based on fractional variation theory compared with the traditional image denoising algorithm could better retain the edge and texture detail information, obtain visual effect, and properly improve the signal-to-noise ratio.
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Acknowledgment
This work is supported by Sichuan province science and technology department application foundation project (2016JY0238) and Scientific Research Fund of Sichuan Province Education Department(18ZA0363,18ZB0374, 18ZB0376) and Key Research Base for Social Science in Sichuan Province-Sichuan Tourism Development Research Center Project (LYC15-09).
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Huang, G., Chen, Ql., Men, T., Zhang, XQ., Qin, HY., Xu, L. (2019). Application in Image Denoising Using Fractional Total Variation Theory. In: Jiang, M., Ida, N., Louis, A., Quinto, E. (eds) The Proceedings of the International Conference on Sensing and Imaging. ICSI 2017. Lecture Notes in Electrical Engineering, vol 506. Springer, Cham. https://doi.org/10.1007/978-3-319-91659-0_15
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DOI: https://doi.org/10.1007/978-3-319-91659-0_15
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