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A Traffic Image Dehazing Method Based on Improved Generative Adversarial Network

A technology for generating images and images, applied in biological neural network models, image enhancement, image analysis, etc., can solve the problems of unsatisfactory defogging effect, loss of details, and color distortion in dense fog areas, so as to avoid color distortion and halo effect, improve quality, improve the effect of defogging effect

Active Publication Date: 2022-06-21
FUZHOU UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] In view of this, the object of the present invention is to propose a traffic image defogging method based on an improved generative confrontation network, which can solve the problems of color distortion, loss of detail and unsatisfactory defogging effect in dense fog areas when the traffic image is defogged. question

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  • A Traffic Image Dehazing Method Based on Improved Generative Adversarial Network

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[0067] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0068] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0069] It should be noted that the terminology used herein is for the purpose of describing specific embodiments only, and is not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural as well, furthermore, it is to be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates that There are features, steps, operations, devices, components and / ...

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Abstract

The invention provides a traffic image defogging method based on an improved generative confrontation network, comprising the steps of: establishing a traffic image defogging data set; building a generator network and a multi-scale discriminator network based on mixed attention, and optimizing a loss function; Use the established traffic image dehazing dataset to train a hybrid attention-based generator network and a multi-scale discriminator network; input the image that needs to be dehazed into the trained generator network to obtain the dehazed image. The invention can solve the problems of color distortion, detail loss and unsatisfactory defogging effect in dense fog areas when the traffic image is defogged.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence and image processing, in particular to a traffic image dehazing method based on an improved generative confrontation network. Background technique [0002] With the acceleration of industrialization and urbanization in my country and the deterioration of the natural environment, haze weather has become a common disastrous weather. Haze is formed by the scattering and refraction of light passing through it by water droplets or a large number of tiny particles suspended in the air, causing blurring, low contrast and saturation, and color attenuation of images collected in outdoor scenes, affecting people. The visual perception of the eye further affects the imaging effect of outdoor vision systems such as security monitoring, military survey, and intelligent transportation, and increases the difficulty of subsequent visual processing such as detection, segmentation, and identificatio...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06N3/04G06N3/08
CPCG06T5/003G06N3/084G06T2207/10004G06T2207/10024G06T2207/20081G06T2207/20084G06N3/048
Inventor 张立伟张增辉何炳蔚
Owner FUZHOU UNIV