Research On Characteristic Analysis And Clarification Methods Of Degraded Video Images

In recent years,severe weather such as smog has caused frequent degradation of the video images taken under this condition,problems such as loss of image details,reduced contrast,and color distortion.The effectiveness and availability of video images have been greatly reduced.,Traffic control and other aspects have caused serious impacts,so the clear processing of degraded video images has great application value.Based on the purpose of adaptive defogging,the paper starts from the perspective of image enhancement,analyzes the characteristics of degraded video images,and defogs the actual fogging of foggy video images.The main work and results are as follows:(1)Analysis of the characteristics of degraded video images.The degraded and non-degraded video images are compared and analyzed,and the differences between the two are analyzed.The characteristics are extracted from four aspects:color attenuation characteristics,contrast characteristics,time-frequency domain characteristics,and depth of field characteristics.The relationship of image quality has laid the foundation for the subsequent algorithms to be clear.(2)Research on adaptive Retinex algorithm based on color attenuation prior.The principle and steps of the Retinex image defogging algorithm are mainly studied,and through the analysis and research on the characteristics of degraded video images,a linear model of depth information and Gaussian scale parameters is established to achieve adaptive Retinex defogging processing of the luminance component At the same time,the saturation adaptive linear stretching algorithm is used to optimize the saturation component,and the adaptive processing of foggy images is realized.Finally,it is verified by MATLAB simulation experiments.The results show that the algorithm can better repair the original color of the image while highlighting the details of the image,and can effectively improve the effect of the uneven fog density on the video image.(3)Research on video defogging model combining key frame and adaptive Retinex algorithm.For the research of video dehazing,there are often problems of time constraints and brightness consistency.In view of the problems in the process of video defogging,the correlation between video sequence images is studied,and considering the characteristics of static scenes and videos with moving target scenes,a combination of key frames and adaptive Retinex algorithm is proposed.Video defog model.The model uses the correlation between video frames to select key frames,combined with the adaptive Retinex algorithm to calculate the depth of field information and illuminance components of key frames,determine the reference information of the video frames to be processed through the threshold,and perform the corresponding defogging process,To achieve the purpose of video defogging.Finally,the results of video defogging are compared and analyzed through simulation experiments,and the effectiveness of the video defogging model and algorithm is demonstrated.