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

A convolutional neural network, single image technology, applied in the field of computer vision, can solve the problems of outdoor computer vision system impact, image imaging quality impact, image blur, etc., to improve visual effects, high detail retention, high SSIM value Effect

Inactive Publication Date: 2020-02-04
HARBIN UNIV OF SCI & TECH
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Problems solved by technology

[0002] Rainy days will affect the imaging quality of the image, making the image blurred, d

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

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[0037] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific examples. These examples are illustrative only and not limiting of the invention.

[0038]The present invention proposes a multi-channel multi-scale convolutional neural network rain removal algorithm. The specific implementation steps of the method are: the data set used for network training and testing comes from the public synthetic rainy image data set Rainy_image_dataest, and the data set includes 1,000 real rain-free images and 14,000 synthetic rainy images composed of rain lines of different directions and sizes added to these rain-free images. After the training, the test is performed on the synthetic rainy image and the real rainy image respectively, and compared with the rain removal effect of other algorithms. During training, 9000 images ...

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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...

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Application Information

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IPC IPC(8): G06T5/00G06T5/50G06N3/04
CPCG06T5/005G06T5/50G06N3/045
Inventor 柳长源王琪张一帆何先平
Owner HARBIN UNIV OF SCI & TECH
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