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Single Image Deraining via Rain-Steaks Aware Deep Convolutional Neural Network by Zheng, Chaobing; Li, Yuwen; Wu, Shiqian is a scholarly article available to read on EtoBox.

What is Single Image Deraining via Rain-Steaks Aware Deep Convolutional Neural Network about?

It is challenging to remove rain-steaks from a single rainy image because the rain steaks are spatially varying in the rainy image. This problem is studied in this paper by combining conventional image processing techniques and deep learning based techniques. An improved weighted guided image filter (iWGIF) is proposed to extract high frequency information from a rainy image. The high frequency information mainly includes rain steaks and noise, and it can guide the rain steaks aware deep convolutional neural network (RSADCNN) to pay more attention to rain steaks. The efficiency and explain-ability of RSADNN are improved. Experiments show that the proposed algorithm significantly outperforms state-of-the-art methods on both synthetic and real-world images in terms of both qualitative and quantitative measures. It is useful for autonomous navigation in raining conditions.

Author

Zheng, Chaobing; Li, Yuwen; Wu, Shiqian

Published

2022

Language

EN