Method and system for processing traffic monitoring video image in foggy day

Abstract

A method for processing a traffic monitoring video image in a foggy day includes: 1, detecting vehicles in traffic monitoring scene; 2, building area-of-interest, namely a driving area according to detected vehicle and pedestrian movement areas; 3, estimating road area depth ratio, and generating a depth image: estimating the road area depth ratio according to detected sizes, positions and moving directions of vehicles, building a traffic monitoring scene model, and generating a traffic monitoring scene depth image automatically; 4, building a traffic monitoring scene foggy day image degradation model: using the traffic monitoring scene depth image as an important parameter of foggy day image degradation, and building the traffic monitoring scene foggy day image degradation model; and 5, solving the traffic monitoring scene foggy day image degradation model, and recovering an image.

Description

technical field [0001] The invention relates to the field of intelligent transportation, in particular to a method and a system for processing video images of traffic monitoring in foggy days, which perform defogging processing on traffic monitoring videos in foggy days. Background technique [0002] Intelligent transportation has high requirements on the quality of image information collection and processing. However, video surveillance in the field of intelligent transportation is still not perfect. Therefore, even with the most advanced image acquisition equipment, it may not really be effective due to the interference of various environmental factors during the shooting process. The problem of image recognition in foggy weather is one of them. The problems of traffic video surveillance in foggy conditions mainly include: (1) In foggy conditions, the blurred image information is not conducive to the identification of the required traffic information by the monitoring per...

AI Technical Summary

Problems solved by technology

But today's video surveillance in the field of intelligent transportation is still not perfect

Therefore, even with the most advanced image acquisition equipment, it may not be effective due to the interference of various environmental factors during the shooting process, and image recognition problems in foggy conditions are one of them.

The problems of traffic video surveillance in foggy weather mainly include: (1) In foggy weather, blurred image information is not conducive to the monitoring personnel’s recognition of the required traffic information. Control and evidence collection of traffic violations, accidents, etc. will also be extremely disadvantageous

(2) When computer monitoring is used for monitoring, the monitored object may not be intelligently recognized due to the reduction of contrast, or the recognition error may be caused by the reduction of image quality

Restoration methods based on depth information estimation usually only use the grayscale information or color information of the image, and the accurate estimation of depth information may lack reliability. The degradation model provides precise parameters that affect the defogging accuracy

It is even necessary to use expensive hardware devices such as radar or distance sensors to obtain accurate scene depth information, which limits the wide application of such methods in solving practical problems

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