A Retinex-Based Variational Model for Enhancement and Restoration of Low-Contrast Remote-Sensed Images Corrupted by Shot Noise
Author:
Funder
Science and Engineering Research Board
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Atmospheric Science,Computers in Earth Sciences
Link
http://xplorestaging.ieee.org/ielx7/4609443/8994817/09016022.pdf?arnumber=9016022
Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. RDC-UNet++: An end-to-end network for multispectral satellite image enhancement;Remote Sensing Applications: Society and Environment;2024-11
2. A weighted nuclear norm (WNN)-based retinex DIP framework for restoring aerial and satellite images corrupted by gamma distributed speckle noise;Multimedia Tools and Applications;2023-10-02
3. Restoration and Enhancement of Aerial and Synthetic Aperture Radar Images Using Generative Deep Image Prior Architecture;PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science;2022-11-14
4. Multispectral Image Enhancement Based on the Dark Channel Prior and Bilateral Fractional Differential Model;Remote Sensing;2022-01-05
5. A retinex based non-local total generalized variation framework for OCT image restoration;Biomedical Signal Processing and Control;2022-01
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