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Domain adaptive defogging method based on generative adversarial network

A domain-adaptive, network technology, applied in the field of domain-adaptive dehazing based on generative adversarial networks, to achieve the effects of enhancing visibility, eliminating adverse weather effects, and increasing recognition

Pending Publication Date: 2021-03-02
LIAONING UNIVERSITY OF PETROLEUM AND CHEMICAL TECHNOLOGY
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Problems solved by technology

The present invention aims to solve the existing problems of these video defogging processing techniques

Method used

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  • Domain adaptive defogging method based on generative adversarial network
  • Domain adaptive defogging method based on generative adversarial network
  • Domain adaptive defogging method based on generative adversarial network

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Embodiment Construction

[0019] In order to make the purpose, features and advantages of the invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0020] see figure 1 , in severe weather conditions such as haze and low visibility, the blurred video images acquired by the video acquisition equipment are transmitted to the video image processing module group DF-CNN, and the video image processing is performed in the video image processing module group, and finally the clear defogged video The image is visualized on the monitor.

[0021] The composition of the video image processing module group DF-CNN is as follows. Inside the dehazing model, it consists of a foggy image preprocessing module and a dehazing module. The foggy image preprocessing module mainl...

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Abstract

The invention discloses a real-time video defogging method, and the method comprises the steps: obtaining a foggy video through a camera, inputting the video into a video image processing module groupDF-CNN, processing each frame of blurred image in the video, and enabling a defogging model to comprise a foggy day image preprocessing module and a defogging module, A Cycle-GAN generative adversarial network structure is mainly adopted for image preprocessing, a defogging module is mainly composed of a coarse-scale convolutional neural network, a fine-scale convolutional neural network and an encoder decoder network structure, a clear image is obtained after model processing, and finally a processing result is synthesized into a clear video image to be visualized through a display terminal.The system has a better processing effect, has real-time processing capability, and achieves a high-speed and high-definition defogging effect.

Description

technical field [0001] The invention mainly relates to the field of computer image and video processing, in particular to a domain adaptive defogging method based on a generating confrontation network. Background technique [0002] Smog is a common weather phenomenon in cities. Many areas in my country have used smog as disastrous weather for early warning and forecasting, and high-density population areas will inevitably emit a large amount of fine particles. Once the emission exceeds the atmospheric circulation capacity and carrying capacity At this time, if affected by the static and stable weather, large-scale smog will easily appear. When the smog is severe, the visibility of the road is low, and the road information obtained by the driver is seriously insufficient. Traffic accidents are prone to occur, and the automatic driving system and target tracking system will be severely restricted. Therefore, restoring clear video images in severe weather such as fog and haze has...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06N3/04
CPCG06T2207/10016G06T2207/20084G06N3/045G06T5/73
Inventor 潘斌汤永恒陈欢杨楠楠田梦娇韩江雪
Owner LIAONING UNIVERSITY OF PETROLEUM AND CHEMICAL TECHNOLOGY
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