Image defogging method based on dark channel information

Abstract

The invention discloses an image defogging method based on dark channel information, belonging to the technical field of image treatment and computer vision. The method disclosed by the invention comprises the following steps of: calculating the minimum value of each pixel of each color channel of an input image via a minimum value filter; then calculating dark channel counting values of the image under different scale parameters and carrying out Gaussian smoothing filter on the dark channel counting value corresponding to each scale parameter; distributing different weight values to the filtered dark channel counting values according to different scale parameters; and carrying out weighted optimization on the dark channel counting values and calculating a transmission coefficient of the scene so that the defogging of the image is realized. The application of the invention can avoid complex soft matting optimization steps and computing complexity of the defogging; the image with high quality can be obtained after the defogging; and the requirement on real-time treatment application can be met.

Description

technical field [0001] The invention belongs to the technical field of image processing and computer vision, and in particular relates to a single image defogging processing method based on dark channel information. Background technique [0002] Foggy image restoration is a key technology in the technical fields of image processing and computer vision. Because the classic computer vision algorithms often assume that the input image is the reflected light on the surface of the object, for some foggy images, the mathematical models of these methods will inevitably fail to a certain extent, thus affecting the final image defogging effect. Therefore, it is of great significance to study the imaging degradation model and dehazing method of foggy images. [0003] For a single foggy image, the existing image defogging methods are usually based on the prior information rules of the foggy image. Typical methods are Tan method (local contrast maximization method), Fattal method (sce...

AI Technical Summary

Problems solved by technology

Although the dehazing quality of the image recovered by the He method is relatively ideal, only one scale parameter is considered, and the calculation is extremely complex and the soft matting optimization method is used to estimate the transmission coefficient of the scene, and the calculation amount will appear as the image size increases. The geometric level increases, and it is difficult to achieve real-time processing of fog image removal on the basis of existing hardware, and it is difficult to apply it to practical applications

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