A method for enhancing vision of intelligent vehicle in smog weather

Abstract

A method for enhancing vision of intelligent vehicle in smog weather includes converting image from RGB color space to HSV color space; 2) evaluating the smog concentration; 3) calculating atmosphericcoverage parameters; 4) obtaining a foreground image Ivis (x); 5) the current smog concentration is obtained by the directional filtering algorithm of the luminance channel as the background image, the image noise is removed by the Gaussian filter, and the influence of the atmospheric coverage parameters on the foreground image is increased; 6) according to step 5), outputting vision enhancementresult. The invention can effectively improve the contrast and clarity of the video, at the same time, has higher compute efficiency, effectively improves the image quality of the video signal, enhances the sensitivity, thus ensuring the safety and comfort of unmanned manipulation.

Description

technical field [0001] The invention relates to the field of vision enhancement, in particular to a vision enhancement method for a smart car in haze weather. Background technique [0002] The current computer vision system on the road is very sensitive to weather conditions, among which, the fog and haze weather conditions are the most serious one to the visual impact of various weather conditions. Under foggy weather conditions, the visibility is greatly reduced, the visibility of the road environment system becomes poor, and the obtained image is severely degraded, not only blurred, the contrast is reduced, but also serious color shift and distortion occur. Many features contained in the image are covered, which greatly reduces the application value of the image, and also makes these visual systems unable to work normally. [0003] In recent years, the sharpening processing of hazy images has become a research hotspot in the field of computer vision and image processing,...

AI Technical Summary

Problems solved by technology

However, due to the complexity and randomness of weather conditions, some algorithms proposed so far have certain limitations, and some research results and research methods that have been obtained are still in continuous development and need to be further perfected and improved.

In the prior art, aiming at the degradation of images collected by the road vision system in fog and haze, no effective image enhancement method in fog and haze has been found, so that image enhancement can be effectively realized in fog and haze weather, and the video signal can be effectively improved. image quality and increased sensitivity

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