Single-image rain removing method of multi-channel multi-scale convolutional neural network

Abstract

The invention relates to a single-image rain removing method of a multi-channel multi-scale convolutional neural network. A multi-channel multi-scale convolutional neural network is established and used for extracting feature information of a rainy image and mapping the feature information to the direction of a rainless image. Firstly, a rain image is decomposed through guided filtering, and a low-frequency background image and a higher-frequency rain line image are obtained; and then the low-frequency background image and the higher-frequency rain line image are sent to a convolutional neuralnetwork for feature learning to obtain a rain line-removed low-frequency image and a rain line-removed higher-frequency image, and finally the rain line-removed low-frequency image and the rain line-removed higher-frequency image are fused to obtain a rain line-removed image. In the convolutional neural network, a multi-scale feature map is extracted from a low-frequency background image and a higher-frequency rain line image. And meanwhile, when the network model is constructed, the multi-scale feature information of the image is extracted by using hole convolution instead of common convolution, so that richer image features are obtained, and the rain removal performance of the algorithm is improved. Experiments prove that the rain line in the image can be effectively removed, and the rain-removed image is clear and high in detail retention degree.

Description

technical field [0001] The invention relates to the field of computer vision, and relates to a method for removing rain from a single image of a multi-channel multi-scale convolutional neural network. Background technique [0002] Rainy days will affect the imaging quality of the image, making the image blurry, distorted, and poor visibility. This will affect the work of outdoor computer vision systems. Therefore, the research of image deraining algorithm is paid more and more attention by researchers from all over the world. Image rain removal is the preliminary work of algorithms in the fields of target recognition and target tracking. It is of great help to improve the performance of such algorithms. Image rain removal has great application prospects in the field of machine vision. [0003] In recent years, the image rain removal algorithm has attracted more and more researchers' attention. At present, the rain removal algorithm is mainly divided into two categories. Th...

AI Technical Summary

Problems solved by technology

[0002] Rainy days will affect the imaging quality of the image, making the image blurred, deformed, poor visibility, etc.

This will affect the work of outdoor computer vision systems

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