Highlight image enhancement method and device based on dark channel prior mirror surface and storage medium

Abstract

The invention discloses a mirror surface highlight image enhancement method and device based on dark channel prior, and a storage medium. The method comprises the steps: selecting the most fuzzy pixelin an input image, employing a moving window minimum filter to filter each color channel of the pixel, obtaining the maximum value of the color channel, and enabling the maximum value to serve as anestimation value of an atmospheric light component; calculating the chromatic aberration of the local pixels on the boundary constraint to construct a weighting function, and constructing a refined target function of the scene transmittance according to the weighting function; based on the improved guided filtering optimization objective function, outputting a final image based on the optimized transmissivity and the estimated value of the atmospheric light component; processing the final image by using contrast-limited adaptive histogram equalization, and improving local details of the localcontrast-enhanced specular highlight image. According to the method disclosed in the invention, the definition and color features of the image are effectively enhanced, and the problem that the texture information of the highlight shielded area in the image is lost is solved.

Description

technical field [0001] The invention relates to image enhancement technology, and belongs to the field of image processing, in particular to a dark channel prior specular highlight image enhancement method, device and storage medium. Background technique [0002] In the field of computer vision, most algorithms assume that the surface of the object is an ideal diffuse reflection surface, regardless of the influence of specular reflection. In the real world, the specular reflection phenomenon, that is, the highlight phenomenon, must exist. The highlight phenomenon represents the chromaticity information of the light source, and can be regarded as the surface feature of the object in terms of visual effects. The existence of highlights in the image often covers the texture of the object surface, damages the outline of the object edge, changes the color of the object surface, and directly leads to the loss of information in the local area of ​​​​the object surface. The highlig...

AI Technical Summary

Problems solved by technology

[0004] First, there are restrictions on the input image. The input image needs to be a specular highlight image taken in a specific scene, and the application scene is relatively single;

[0005] Second, for specular highlight images randomly captured in real-life scenes, the existing algorithms cannot remove the highlight components in the image very well, and the processed image will have the problem of information loss. Its popularity and practicability There are still some limitations

Images