A method and apparatus for image rain removal

Abstract

The invention provides an image rain removing method and a device, comprising: an image to be detected with raindrops is separated into a high-frequency component image and a low-frequency component image; the high-frequency component image is input to the trained convolution neural network with residual structure, and the rain-free image is outputted; the rain-free image is synthesized with the image to be detected, and the rain-free image is obtained; the rain-free image is inputted to the trained convolution neural network with discriminant structure, and the category of the rain-free imageand the raindrop-free image corresponding to the image to be detected are outputted; the category is inputted to the convolution neural network with a residual structure, and the parameters of the convolution neural network with residual structure are updated to obtain the final rain-free image. The final rain-free image obtained by the invention retains the texture details of the rain-free areain the image to be detected, so that the final rain-free image is close to the rain-free image corresponding to the image to be detected, and the important factors in the image to be detected are wellretained.

Description

technical field [0001] The invention relates to the technical fields of image processing and machine learning, in particular to a method and device for removing rain from an image. Background technique [0002] With the rapid development of machine learning technology and the maturity of image processing technology, the outdoor computer vision system can obtain a large amount of rich and high-resolution image information in time due to its accuracy, speed, reliability, intuitive, real-time and comprehensive reflection of the monitored object, etc. Advantages, especially in occasions that are not easy to be directly observed by humans, it can solve the problem of manual observation, and is widely used in various fields, such as car driverless or remote monitoring systems. However, in real life, in rainy and snowy weather Under the influence of light and refraction, objects in the image are easily blurred and blocked by separate rain marks, so rain and snow have a great impact...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem that the current image deraining method based on deep learning will smooth the texture details of the rainless area in the rain image, and at the same time cannot cover some important factors in the real rain image well, the present invention provides an image deraining method methods, including:

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