Fast Dehazing Method With Joint Minimum Filter And Bilateral Filter

Dehazing of video images is an important research content of image processing and is widely used in video-assisted transport,driver assistance systems,remote sensing and outdoor video surveillance.In this paper,we study the fast dehazing method based on the atmospheric model and the joint minimum filter and bilateral filter.The main research work and research progress of the paper are as follows:1.For the problem that the color attenuation prior model has the error of restoring the scene depth map,a joint minimum filter and bilateral filtering method are proposed to process the depth map.With the assumption that the local depth of field is invariable,the values of scene depth of neighboring pixels are equalized,bilateral filtering is used to eliminate the blocky effect,and the problem that near white areas are mistakenly considered to be distant in the depth map is solved.The dehazing effect is improved while ensuring the algorithm's operation speed.Simulation experiments verify the effectiveness of the method.2.For the disadvantages of the calculation amount and the complexity of the single image dehazing algorithm framework,a fast dehazing method with joint minimum filtering and bilateral filtering is proposed.The bilinear interpolation method is used to reduce the image and make the calculation amount smaller;after obtaining the required transmission map,the transmission map is enlarged.It solves the picture stall problem caused by slow operation.Simulation results show that this method improves the real-time performance of single image dehazing.3.We set up a real-time video processing system.The color video is input from the visible light camera,transmitted to the computer through the network port,and is subjected to dehazing processing and then output to the display,and the PTZ is remotely controlled through the network cable;A real-time dehazing platform software adapted to the windows platform and capable of long-time operation is developed.The performance of the proposed dehazing method was verified by systematic experiments.Evaluations were made using evaluation indicators such as color distortion and visible edges.