Image defogging method based on dark channel and bright channel priori

Abstract

The invention discloses an image defogging method based on dark channel and bright channel priori. The method comprises the following steps of establishing an atmospheric light scattering model basedon the physical model of an degraded image; taking an atmospheric light value as a global variable; performing prior estimation on an atmospheric light scattering model in combination with a dark channel and a bright channel to obtain an atmospheric light value; obtaining coarse transmissivity according to the atmospheric light scattering model and the obtained atmospheric light value to acquire more accurate data; then, using the gray level image of the original image as a guide image to carry out guide filtering to refine the transmissivity, thereby reserving the edge information of the depth of field, while reducing the time complexity of the algorithm, finally, acquiring the transmissivity through self-adaptive adjustment according to the self-adaptive transmissivity compensation function, sky region segmentation is not needed, the color distortion problem of a bright area is avoided, and the self-adaptability of the algorithm is improved. The problem of distortion of the color ofthe bright area during foggy image recovery is effectively solved, the defogging effect is natural, and the contrast ratio of the image is remarkably improved.

Description

technical field [0001] The invention belongs to image processing methods, in particular to an image defogging method based on dark channel and bright channel priors. Background technique [0002] Smog causes the quality of the image captured by the imaging device to decline, which in turn seriously affects the analysis and judgment of the visual system. Therefore, automatic algorithms that improve the visibility of foggy images to obtain better visual effects and richer detail information have become the focus of many researchers. So far, many researchers have proposed many methods for processing foggy images. According to different dehazing principles, the current methods can be divided into two categories: image dehazing methods based on image enhancement and image dehazing methods based on image restoration. Image enhancement mainly includes Retinex transform, histogram equalization, wavelet transform and other methods. Image restoration-based image defogging methods m...

AI Technical Summary

Problems solved by technology

Although researchers at home and abroad have done a lot of research and innovation and achieved certain results, there are still various problems. The prior defogging method for dark channels is not suitable for the sky and large white areas. Atmospheric light estimation is easy to be too large, resulting in color distortion and other problems

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