Research On Adaptive Variational Model Of Image Dehazing

Nowadays,the environmental pollution is becoming more and more serious,and the quality of the environment in many cities is getting worse and worse,causing fog and haze weather is also very common.However,the effects of haze weather can make the visual image degenerate,such as the decline of contrast,the loss of the original color information,the inaccuracy of color and so on.In this way,the feature information we want to get will be lost or blurred,which will also have a great impact on subsequent image manipulation.Image de fog is a very important part of image processing.It is now applied to outdoor surveillance video,pilotless,military exploration and other fields.Therefore,the algorithm of image restoration for foggy image is studied.In order to reduce the impact of haze on image acquisition equipment,it has great practical significance.Firstly,the imaging mechanism of the fog image is analyzed and the existing image dehazing algorithm is classified,and the principle of the most mainstream image dehazing algorithm is mastered.Because the image de fog method based on image enhancement does not consider the cause of image degradation,the restored image will have some loss of details,so we model the fog based on the physical model.The basic idea is that the foggy image is fuzzy and I keep the original image information on the premise of me.We want to increase the contrast to restore the color information of the image,and we add a PM diffusion term to enhance the details of the edges and textures in the image.In theory,a variational image dehazing model is proposed on the basis of the above thought.In this paper,the existence and uniqueness of the solution of the corresponding evolution equation is proved.First,the sub differential is used to define the weak solution and the regularization evolution equation,and the instability and non convexity are solved,and a weak solution of the regularization equation is obtained and the solution is obtained.The limit in the definition of the weak solution of a regular equation is proved by Schauder theorem,and the existence of weak solutions is proved.In this paper,we use the property of the equation itself and the Gronwall inequality to prove the uniqueness of the understanding.In the numerical aspect,the finite difference dispersion scheme is given,which is realized by MATALB software.For contrast enhancement,we carry out Taylor expansion and use fast Fourier transform,which can reduce the number of convolution,and compare with the classic fog model,and carry out an experimental analysis.The experimental results show that the model is superior to the classical fog removal model in terms of experimental time and effect.