Single Image Deraining via Feature-based Deep Convolutional Neural Network Article Swipe
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2305.02100
It is challenging to remove rain-steaks from a single rainy image because the rain steaks are spatially varying in the rainy image. Although the CNN based methods have reported promising performance recently, there are still some defects, such as data dependency and insufficient interpretation. A single image deraining algorithm based on the combination of data-driven and model-based approaches is proposed. Firstly, an improved weighted guided image filter (iWGIF) is used to extract high-frequency information and learn the rain steaks to avoid interference from other information through the input image. Then, transfering the input image and rain steaks from the image domain to the feature domain adaptively to learn useful features for high-quality image deraining. Finally, networks with attention mechanisms is used to restore high-quality images from the latent features. Experiments show that the proposed algorithm significantly outperforms state-of-the-art methods in terms of both qualitative and quantitative measures.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2305.02100
- https://arxiv.org/pdf/2305.02100
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4368755544
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4368755544Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2305.02100Digital Object Identifier
- Title
-
Single Image Deraining via Feature-based Deep Convolutional Neural NetworkWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-05-03Full publication date if available
- Authors
-
Chaobing Zheng, Jun Jiang, Wenjian Ying, Shiqian WuList of authors in order
- Landing page
-
https://arxiv.org/abs/2305.02100Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2305.02100Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2305.02100Direct OA link when available
- Concepts
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Feature (linguistics), Computer science, Artificial intelligence, Image (mathematics), Convolutional neural network, Domain (mathematical analysis), Pattern recognition (psychology), Image quality, Computer vision, Mathematics, Linguistics, Philosophy, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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