Improvement And Simulation Of Dehazing Algorithm For Fog Image

In foggy weather,due to the scattering effect of particles in the air,the images taken by the outdoor imaging device have quality problems such as decreased contrast and unclear image,which makes it difficult to process the image after the feature extraction and target recognition.The normal operation of the associated vision system has a serious impact.Therefore,the study of image dehazing methods has important theoretical and practical significance.In this paper,the research status of image dehazing technology at home and abroad is introduced from the aspects of image restoration and image enhancement.The atmospheric scattering model is introduced to explore the essential causes of foggy image degradation.On this basis,the dark channel prior algorithm is introduced.Multi-scale Retinex algorithm and homomorphic filtering image enhancement algorithm,and simulation analysis and comparison of each algorithm.In view of the deficiencies of the algorithms,two improved algorithms are proposed in this paper.The image quality evaluation methods combined with subjective and objective methods are used to evaluate the image effects processed by the algorithm.Aiming at the high time complexity and halo phenomenon of dark channel dehazing algorithm,this paper proposes an improved algorithm based on dark channel prior image dehazing.In the improved algorithm,the pilot filtering and the minimum filtering method are firstly used to optimize the transmittance estimation,and then the image is converted from the RGB color space to the color space HSV.For the multi-scale Retinex algorithm,the image is easy to appear whitening problem.The filter function replaces its original surround function and uses it to process the il uminance component,uses gamma nonlinearization to correct the brightness of the incident component,and final y outputs the image to the RGB color space.The image processed by the improved algorithm has full color,clear image,reduced noise interference and suppressed halo phenomenon,which reduces the time complexity to a certain extent and has a good effect on mist image processing.Aiming at the problem of homomorphic filtering algorithm,this paper proposes an improved algorithm based on homomorphic filtering image dehazing.The improved homomorphic filtering algorithm is used to adjust the brightness of uneven il umination image,and the nonlinear problem is transformed by logarithmic operation.The linear problem is solved,and the high and low frequency components are processed separately.The low-frequency information is first suppressed by the high-pass filter,and the low-frequency information is equalized by the histogram equalization,and the pixel values of the region are redistributed by nonlinear stretching.The improved algorithm enhances detail and edge information,improves image contrast,and enhances the visibility of dense fog images.