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Removal of Noise and Artifacts

2011
Several types of noise and artifacts affect the quality of images obtained even with imaging systems of the highest quality and under the most carefully designed experimental conditions. As a consequence, the removal of noise and artifacts is an important preprocessing step in the analysis of images; see Rangayyan [6] for detailed discussions on ...
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Notice of Removal Low-frequency image noise removal using white noise filter

2016 IEEE International Conference on Image Processing (ICIP), 2016
Meisam Rakhshanfar, Maria A. Amer
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Variational-Based Mixed Noise Removal With CNN Deep Learning Regularization

IEEE Transactions on Image Processing, 2020
Faqiang Wang, Jun Liu
exaly  

Mixed Noise Removal by Weighted Encoding With Sparse Nonlocal Regularization

IEEE Transactions on Image Processing, 2014
Jielin Jiang, Lei Zhang, Jian Yang
exaly  

Mixed Noise Removal via Laplacian Scale Mixture Modeling and Nonlocal Low-Rank Approximation

IEEE Transactions on Image Processing, 2017
Weisheng Dong, Xuemei Xie, Guangming Shi
exaly  

Thin cloud removal from optical remote sensing images using the noise-adjusted principal components transform

ISPRS Journal of Photogrammetry and Remote Sensing, 2019
Meng Xu, Xiuping Jia, Mark Pickering
exaly  

Models for Multiplicative Noise Removal

2021
Xiangchu Feng, Xiaolong Zhu
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A Doubly Degenerate Diffusion Model Based on the Gray Level Indicator for Multiplicative Noise Removal

IEEE Transactions on Image Processing, 2015
Zhenyu Zhou, Zhichang Guo, Jiebao Sun
exaly  

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