.png){kind=icon}
返回
Single image deraining using deep convolutional networks
.png){kind=icon}
PRE
AI
DOI：10.1007/s11042-018-5825-8.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A deep learning-based single image deraining algorithm is proposed in this work. Instead of modeling a rain layer as a linear function between the rain image and its clear version as previous works do, we directly formulate the clear image as the result of a non-linear mapping of thrain image. We construct a coarse deraining convolutional network and a refinement convolutional network to learn this non-linear mapping function. The coarse deraining network is trained to detect the rain streaks with different directions, and restore a raw derained result. The refinement network aims at refining the result according to the raw derained image and the original rain image. By combining the two networks, we are able to well-restore the rain-free image. Experimental results demonstrate that the proposed deraining method can produce high-quality clear images from both synthetic and real-world rain images, outperforming the state-of-the-art methods qualitatively and quantitatively.
Keyword:
Image deraining
image restoration
image enhancement
deep learning
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3
论文数:
2.0W
被引数:
3.2W
机构
引用论文
.png){kind=icon}
分享收藏分享收藏
分享收藏
查看更多内容