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Ground Nephogram Enhancement Algorithm Based on Improved Adaptive Fractional Differentiation

Xiaoying Chen1,*, Jie Kang1, Cong Hu2

1 College of Mechanical & Electrical Engineering, Sanjiang University, Nanjing, 210012, China
2 Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin University of Electronic Technology, Guilin, 541004, China

* Corresponding Author:Xiaoying Chen. Email: email

Journal of New Media 2021, 3(4), 151-180. https://doi.org/10.32604/jnm.2021.024665

Abstract

The texture of ground-based nephogram is abundant and multiplicity. Many cloud textures are not as clear as artificial textures. A nephogram enhancement algorithm based on Adaptive Fractional Differential is established to extract the natural texture of visible ground-based cloud image. GrunwaldLentikov (G-L) and Grunwald-Lentikov (R-L) fractional differential operators are applied to the enhancement algorithm of ground-based nephogram. An operator mask based on adaptive differential order is designed. The corresponding mask template is used to process each pixel. The results show that this method can extract image texture and edge details and simplify the process of differential order selection.

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Cite This Article

X. Chen, J. Kang and C. Hu, "Ground nephogram enhancement algorithm based on improved adaptive fractional differentiation," Journal of New Media, vol. 3, no.4, pp. 151–180, 2021.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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