A High-Fidelity Image Dehazing Method

Abstract

The invention discloses a high-fidelity image defogging method. The first step is to perform color enhancement in the HSV space to obtain a color enhanced image. The second step is to perform detail enhancement in the RGB space and use the Butterworth filter to perform image processing in the RGB space. Filtering process, after filtering, the image is converted from RGB space to HSV space to obtain a detail-enhanced image; Step 3: Use rules to perform weighted fusion of the obtained color-enhanced image and detail-enhanced image; the method proposed by the present invention performs color enhancement in HSV space , enhance details in RGB space, and finally fuse the two parts. In HSV space, by introducing adjustment factors, the problems of color distortion and noise amplification are avoided. In RGB space, the Butterworth filter is used to retain more detailed information. While achieving the same effect, the present invention doubles the computing speed, resulting in better real-time processing; the obtained image contains more details and information, and has more uniform illumination.

Description

Technical field [0001] The invention relates to the field of digital image processing and machine vision, in particular to a high-fidelity image defogging 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., and the quality and demand of human life are gradually improved. These application systems are in line with human life. It is closely related and directly image human life. The reduced air quality and reduced visibility have had a great impact on people's lives and industrial development. Because the light is absorbed and scattered by the turbid medium, pictures taken in bad weather outdoors reduce the intensity of the light, resulting in a change in the intensity of the light received by the optical sensor, and ultimately resulting in a decrease in color fidelity, and seri...

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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