Open Access
ARTICLE
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:
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.
Keywords
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.