Colorful haze image defogging and illumination compensation restoration method

Abstract

The invention discloses a colorful haze image defogging and illumination compensation restoration method. The method mainly solves the problems of restoration result color distortion, halo artifacts and darker halos existing in the prior art. The method comprises the steps of using a dark channel image D (x, y) of a haze image I (x, y) for initially estimating air curtain images, conducting gray opening operation on the dark channel image, and obtaining an air curtain image rough estimation image D' (x, y); taking the dark channel image as a guide image, conducting guide filtering on the air curtain image rough estimation image, and obtaining an air curtain image V (x, y); conducting difference on the haze image and the air curtain image, and obtaining a residual image E (x, y); conducting gray closing operation on a bright channel image B (x, y) of the residual image, and obtaining an illumination component image rough estimation image B' (x, y); taking the bright channel image as a guide image, conducting guide filtering on the illumination component image rough estimation image, and obtaining an illumination component image L (x, y); substituting the illumination component image into an illumination-reflection imaging model, and conducting solving to obtain a restoration result. According to the method, a clear image can be stably restored without calculating ambient light and transmissivity.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to an image restoration method, which can be widely used in the preprocessing of image target detection, identification and tracking. Background technique [0002] Under foggy weather conditions, the scattering effect of particles such as aerosols in the atmosphere reduces the contrast of the collected images and distorts the color; at the same time, under foggy conditions, factors such as light source changes, object shadow coverage, and insufficient exposure will make the scene Insufficient lighting further leads to overall or partial darkening of the collected images, reduced visibility, and blurred details. In conclusion, severely degraded haze images interfere with the identification of image information and subsequent image analysis. In recent years, the restoration of haze images has received extensive attention from academia. [0003] In terms of haze image restoration meth...

AI Technical Summary

Problems solved by technology

The effect of the single-scale Retinex (SSR, Single Scale Retinex) method is easily affected by the size of the scale constant, and the color is easily distorted; the multi-scale Retinex (MSR, Multi-Scale Retinex) method may cause halo artifacts and a large amount of calculation; multi-scale The Retinex color restoration method (MSRCR, Multi Scale Retinex with Color Rendetion) method restores the color of the image that violates the grayscale world assumption, but the color correction effect is not obvious

Kimmel (Kimmel, Ron, et al. "A variational framework for retinex." International Journal of Computer Vision52.1(2003):7-23.) normalizes the existing various Retinex methods into a unified variational form, although The computational complexity is reduced, but it is easy to blur the shadow boundary and produce halo artifacts

[0004] Although the above smog image restoration methods have a certain restoration effect on smog-degraded images, they generally have shortcomings such as color distortion, halo artifacts, and dark images, which lead to the failure of subsequent target detection, recognition, tracking and other processing.

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