Image defogging method and license plate image identification method based on the method

Abstract

The invention discloses an image defogging method and a license plate image identification method based on the method by combining a dark channel optimization defogging method and a two-dimensional hidden Markov model. The image defogging method comprises steps of getting a dark channel for a foggy original image obtained through photographing to obtain an original transmission image, performing optimization on the original transmission image to obtain an optimization transmission image, obtaining a corresponding array, performing second optimization calculation on the original transmission image to obtain a final transmission image, and utilizing the final transmission image to obtain a defogging image. The invention enables the defogging result to be enhanced at the blooming effect at the depth discontinuous part, utilizes the condition transfer probability in the image recognition to perform state switching, reflects the dependence relation in two dimensions of the plane and identifies the English characters and the Arabic numbers. For the font size, font inclination and fouling, the image defogging method is strong in resisting noise.

Description

technical field [0001] The invention relates to the fields of image processing and target recognition, in particular to an image defogging method and a license plate image recognition method based on the method. Background technique [0002] Due to the influence of atmospheric aerosols (suspended particles, fog, haze, etc.), the quality of the captured image is reduced, and the contrast of the image is reduced and the color is distorted. Restoring the contrast and true color of the foggy image is very important in photography and computer vision. important application. First of all, image defogging can increase the visibility of the scene and correct color deviation; secondly, most image processing algorithms are usually based on the fact that the pixel value of the input image is the radiation value of the scene. When the color deviation or contrast decreases, the processing algorithm will be affected. Thirdly, the depth information obtained by the image defogging algorith...

AI Technical Summary

Problems solved by technology

First of all, image defogging can increase the visibility of the scene and correct color deviation; secondly, most image processing algorithms are usually based on the fact that the pixel value of the input image is the radiation value of the scene. When the color deviation or contrast decreases, the processing algorithm will be affected. Adverse effects; again, the depth information obtained by the image defogging algorithm will provide additional data support for many computer vision algorithms

[0003] In recent years, the dehazing method of a single image has made great progress. The processing method based on the prior assumption, the statistical results show that most of the natural scene images conform to this assumption, combined with the physical model of the image, the dark channel method is in the Single image defogging has been widely used, but the defogging effect farther away from the viewpoint is significantly reduced, and image halos appear at depth discontinuities

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