Structural residual learning for single image rain removal

To alleviate the adverse effect of rain streaks in image processing tasks, CNN-based single image rain removal methods have been recently proposed. However, the performance of these deep learning methods largely relies on the covering range of rain shapes contained in the pre-collected training rain...

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Vydáno v:	Knowledge-based systems Ročník 213; s. 106595
Hlavní autoři:	Wang, Hong, Wu, Yichen, Xie, Qi, Zhao, Qian, Liang, Yong, Zhang, Shijun, Meng, Deyu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 15.02.2021 Elsevier Science Ltd
Témata:	Computer architecture Deep learning Experiments Generalization Generalization performance Image processing Interpretability Learning Multi-scale convolutional sparse coding Networks Prior knowledge Rain Regularization Side effects Single image deraining Training Deep learning Generalization performance Single image deraining Interpretability Multi-scale convolutional sparse coding
ISSN:	0950-7051, 1872-7409
On-line přístup:	Získat plný text
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