Image defogging method with high fidelity

Abstract

The invention discloses an image defogging method with high fidelity. The method comprises the steps of S1, enhancing color in an HSV space, and thus obtaining a color enhanced image; S2, enhancing details in a RGB space, using a Butterworth filter to filter the image in the RGB space, after filtering, converting the image from the RGB space to the HSV space, and thus obtaining a detail enhanced image; and S3, implementing weighted fusion on the obtained color enhanced image and the obtained detail enhanced image by using a rule. According to the method provided by the invention, the color enhancement is implemented in the HSV space, the detail enhancement is implemented in the RGB space, and at last the two parts are fused. In the HSV space, by introducing an adjustment factor, the problems of color distortion and noise amplification are avoided. In the RGB space, the Butterworth filter is adopted for reserving more detail information. According to the method of the invention, under the condition of obtaining the same effect, the computation speed is increased by double, and the processing real-time performance is better; the obtained image comprises more details and information, and more uniform illumination is provided.

Description

technical field [0001] The invention relates to the fields of digital image processing and machine vision, in particular to a high-fidelity image dehazing method. Background technique [0002] With the development of science and technology and the improvement of people's living standards, more and more visual systems are used in real life, such as monitoring systems, intelligent transportation systems, etc., the quality and needs of human life are gradually improved, and these application systems are closely related to human life. They are closely related and directly reflect human life. Deterioration of air quality and reduced visibility have a great impact on people's lives and the development of industries. Since the light is absorbed and scattered by the turbid medium, pictures taken in bad weather outdoors will reduce the intensity of the light, resulting in a change in the light intensity received by the optical sensor, which will eventually lead to a decrease in colo...

AI Technical Summary

Problems solved by technology

Due to the light being absorbed and scattered by the turbid medium, the pictures taken outdoors in bad weather will reduce the light intensity, resulting in a change in the light intensity received by the optical sensor, which will eventually lead to a decrease in color fidelity and serious color distortion and cast. shift, and the reduction of image contrast, the loss of image detail information, insufficient clarity, and the recognition of image information is greatly reduced

In addition, most automatic systems rely heavily on the definition of the input image, and degraded images will cause the automatic system to fail to work properly, affecting and limiting highway visual monitoring, intelligent navigation, remote sensing monitoring, etc.

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