Image clarification method in foggy day based on self-adaption cluster color transmission

Abstract

The invention discloses a foggy day image sharpening method transmitted based on the self-adapting cluster color, including the following steps: collecting the source image and the target image information, to respectively perform the decoupling process through the color space; counting the mean and the variance of the source image and the target image to make the statistic characteristics of the source image 'close to' the target image as much as possibly; reverting the calibration source image obtained in the L alpha beta color space into the RGB color space through the L alpha beta color space, to obtain an image transmitting calibration result image; go on clustering the result image obtained through the color transmitting calibration and the target image; performing the similar finding and corresponding; performing the second color transmitting calibration; manually adjusting the number of cluster by second calibration to obtain the final calibration result image. The method of the invention realizes the sharpening process on the shot image in the fog, resumes the effective information in the source image.

Description

technical field [0001] The invention belongs to the technical field of image restoration, and relates to a method for clearing and restoring images under low-contrast and low-information conditions, and in particular to a foggy image clearing method based on adaptive clustering color transfer. Background technique [0002] With the continuous development of computer image processing technology, as well as the urgent needs of monitoring, digital photography and other fields, when people analyze some low-contrast and low-information photos, they need to be able to clear the images to a greater extent and restore them. Some key information in the image. [0003] In my country, heavy fog is a frequent weather condition. In heavy fog, no matter which field of outdoor video surveillance system is used in, all the images captured are low-contrast images with heavy fog interference. The amount of image information is very low, and there are a lot of hard-to-see picture information ...

AI Technical Summary

Problems solved by technology

The amount of image information is very low, and there are a lot of hard-to-see picture information and a considerable part of the detail information that cannot be distinguished at all, and these are sometimes the most needed content of an image. Therefore, under normal circumstances, heavy fog The utilization rate of the following images is quite low, and even in some cases, they have to be treated as waste images without any value of use and analysis

[0004] Under normal circumstances, the method of stretching the contrast is used to sharpen low-contrast images. However, due to the inconsistency of the fog conditions in the actual scene, the degree of stretching required is also very different, and it is difficult Find the mapping relationship between fog conditions and contrast, so in many cases, even if the contrast is manually stretched nonlinearly, it is difficult to achieve better results, which makes image restoration in foggy weather become a tricky question

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