Traffic monitoring image rain removing method based on anisotropic sparse gradient

Abstract

The invention discloses a traffic monitoring image rain removing method based on anisotropic sparse gradient. A mathematical model is shown in the specification, wherein f is a degraded image shot inrainy days, u is a clear image to be restored, v is a rain layer image to be detected, [delta]<x> and [delta]<y> are gradient operators in the vertical direction and the horizontal direction of the image respectively, ||.||<L0> is an L0 norm for counting the number of non-zero elements, and the ||[delta]<x>u||<L0> and the||[delta]<y>u||<L0> are vertical and horizontal gradient regularization termsof the image, and ||v||<L0> is a rain detection regularization term, wherein alpha<1>, alpha<2>, beta<1> and beta<2> are non-zero regularization coefficients, the alpha<1>, the alpha<2> and the beta<1> are image horizontal and vertical and rain information regularization coefficients respectively, and the beta<2> is a regularization parameter of a fidelity term. The parameters alpha<1>, alpha<2>,beta<1> and beta<2> can be adjusted through experiments, and a more effective rain removal effect is obtained. According to the invention, the restored traffic monitoring image not only has better edge structure information, but also can effectively measure the position of rain in the image.

Description

technical field [0001] The invention relates to the field of traffic monitoring image processing, in particular to a method for removing rain from traffic monitoring images based on anisotropic sparse gradient. Background technique [0002] In terms of traffic safety management, the video surveillance system can make timely and accurate judgments on traffic violations, violations, traffic jams, traffic accidents and other emergencies. When there is rain in the monitoring scene, obvious rain marks often appear on the video and image taken, resulting in unclear or even lost target features, reducing the target recognition, tracking and monitoring capabilities of the traffic monitoring system, making traffic monitoring It is difficult for the system to exert its real monitoring ability, and even make the system unable to operate normally in severe cases. At present, there are problems such as incomplete rain removal and insufficient protection of characteristic information (su...

AI Technical Summary

Problems solved by technology

When there is rain in the monitoring scene, obvious rain marks often appear on the video and image taken, resulting in unclear or even lost target features, reducing the target recognition, tracking and monitoring capabilities of the traffic monitoring system, making traffic monitoring It is difficult for the system to exert its real monitoring ability, and even make the system unable to operate normally in serious cases

At present, there are problems such as incomplete rain removal and insufficient protection of feature information (such as contour structure) of image targets after rain removal, which cannot meet the actual application requirements.

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