Open Access

ARTICLE

Ground Nephogram Enhancement Algorithm Based on Improved Adaptive Fractional Differentiation

by Xiaoying Chen, Jie Kang, Cong Hu

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:

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

Received 16 September 2021; Accepted 26 October 2021; Issue published 05 November 2021

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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Keywords

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