关键词: 关键词：单幅图像去雨, 频率注意力, 卷积网络, 循环网络, 离散余弦变换

Abstract: Abstract：Rain streaks interfere with the photos the outside vision system takes in rainy weather， which caused lowering the image quality and affecting the subsequent vision tasks. Therefore， for the following computer vision tasks， it is very crucial to remove the rain streaks from the photos and get high-quality images. The goal of the multi-stage rain removal method we present in this research is to recover a high quality image by removing rain streaks from a single rain image using multi-scale frequency attention. Firstly， a multi-stage rain removal model is designed by integrating the variety of rain streaks， decomposing the rain streaks removal process into multiple sub-processes， and eliminating rain streaks step by step. Second， a long and short-term memory recurrent network is improved to achieve multi-stage rain streaks removal， in which the frequency attention mechanism is introduced to strengthen the attention to rain streaks and a multi-scale feature extraction method is designed to characterize the global information. This addresses the issue of oversmoothing in the current rain streaks removal algorithms. The detail restoration module’s final purpose is to fortify background elements. Experiment results show that the proposed algorithm can effectively remove rain streaks on both the synthetic data set and the real dataset while preserving complete background information， and has a good rain removal effect.

Key words: Key words：single image rain removal, frequency attention, convolutional networks, recurrent neural network, discrete cosine transform