Traffic image defogging method based on improved generative adversarial network

An image and network technology, applied in the field of traffic image defogging based on improved generative confrontation network, can solve the problems of unsatisfactory defogging effect, loss of details, color distortion and other problems in dense fog areas, so as to avoid color distortion and halo effect, Improve the quality and improve the effect of defogging effect

Active Publication Date: 2021-05-14
FUZHOU UNIVERSITY
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[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, w

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  • Traffic image defogging method based on improved generative adversarial network
  • Traffic image defogging method based on improved generative adversarial network
  • Traffic image defogging method based on improved generative adversarial network

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

[0068]It should be noted that the following detailed description is exemplary and is intended to provide a further description of the present application. Unless otherwise indicated, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art of this application.

[0069]It should be noted that the terms used herein are intended to describe specific embodiments, and not intended to limit the exemplary embodiments of the present application. As used herein, unless the context further clearly indicates that the singular form is intended to include a plural form, but it should be understood that when the term "including" and / or "including" is used in this specification, it indicates There is a combination of features, steps, operations, devices, components, and / or their combinations.

[0070]Such asfigure 1 As shown, the ...

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Abstract

The invention provides a traffic image defogging method based on an improved generative adversarial network. The method comprises the following steps: establishing a traffic image defogging data set; establishing a generator network and a multi-scale discriminator network based on mixed attention, and optimizing a loss function; training a mixed attention-based generator network and a multi-scale discriminator network by using the established traffic image defogging data set; and inputting an image needing to be defogged into the trained generator network to obtain a defogged image. According to the method, the problems of color distortion, detail loss and non-ideal defogging effect of a dense fog area during defogging of the traffic image can be solved.

Description

technical field [0001] The invention relates to the technical fields of artificial intelligence and image processing, in particular to a traffic image defogging 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 water droplets suspended in the air or a large number of tiny particles that scatter and refract light passing through it, causing blurred images collected in outdoor scenes, low contrast and saturation, color attenuation, etc., affecting people. The visual perception of the eye will further affect the imaging effect of outdoor visual systems such as security monitoring, military survey, and intelligent transportation, and increase the difficulty of subsequent visual processing links such as detection, segmentation, and identification....

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Application Information

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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 UNIVERSITY
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