Iterative dual tree wavelet transform with posterior probability for sar despeckling
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-16821-9.pdf
Reference15 articles.
1. Fracastoro G, Magli E, Poggi G, Scarpa G, Valsesia D, Verdoliva L (2021) Deep learning methods for synthetic aperture radar image despeckling: An overview of trends and perspectives. IEEE Geosci Remote Sens Mag 9(2):29–51
2. Zhang G, Li Z, Li X, Xu Y (2020) Learning synthetic aperture radar image despeckling without clean data. J Appl Remote Sens 14(2):026518–026518
3. Zhou Y, Shi J, Yang X, Wang C, Kumar D, Wei S, Zhang X (2019) Deep multi-scale recurrent network for synthetic aperture radar images despeckling. Remote Sens 11(21):2462
4. Singh P, Shankar A, Diwakar M (2022) Review on nontraditional perspectives of synthetic aperture radar image despeckling. J Electron Imaging 32(2):021609
5. Zhao Y, Liu JG, Zhang B, Hong W, Wu YR (2014) Adaptive total variation regularization based SAR image despeckling and despeckling evaluation index. IEEE Trans Geosci Remote Sens 53(5):2765–2774
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