Research On Image Enhancement Based On Dynamic Saturation Nonlinear Syste

The brightness and contrast level of an image can affect people’s visual perception quality of the image.In reality,due to hardware and software and other factors will produce many low-light images,and the traditional low illumination image enhancement methods pay more attention to the brightness and contrast of the image when processing the image,but ignore the noise problem in the image,resulting in the unsatisfactory effect of image enhancement.Stochastic resonance is a weak signal enhancement method that can transform the noise in the signal into useful information,and this theory has also made a series of research and breakthroughs in the field of image enhancement.However,the image has not completely solved the problem caused by the noise after processing,and some noise will still remain without transforming into useful image information.In this paper,we will take the dynamical saturating nonlinearity as the starting point,and couple the image denoising method to the image enhancement model of the dynamical saturating nonlinearity,so as to improve the brightness and contrast of the image,reduce the noise level in the image and enhance the visual effect of the image.The main contents of this paper are as follows:(1)An image enhancement model coupled with dynamical saturating nonlinearity and anisotropic diffusion filter term of partial differential equation is proposed.Firstly,the differential form of dynamical saturating nonlinearity is introduced,and its image enhancement process in spatial domain is analyzed.Then the anisotropic diffusion filter term of partial differential equation is added to the dynamical saturating nonlinearity as a noise suppression term,and a new image enhancement model is coupled.The new model will suppress the excessive influence of noise on the image information after image enhancement while improving the brightness and contrast of the image,and gradually reduce the noise in the image.In this paper,the anisotropic diffusion filtering terms of two partial differential equations are mainly considered.One is to couple the anisotropic diffusion filtering term in the PM equation to the dynamical saturating nonlinearity,and the other is the YK equation proposed to improve the step effect in the PM equation to obtain the image enhancement model of the dynamical saturating nonlinearity with high-order anisotropic diffusion filtering term.The experimental results show that the dynamical saturating nonlinearity image enhancement model based on partial differential equation can reduce the noise in the image and protect the edge information of the image,so as to make the image perform better in visual effect.(2)An image enhancement model coupled with dynamical saturating nonlinearity and variational regularization term is proposed.In this paper,firstly,the total variational regular term is added to the dynamical saturating nonlinearity to obtain the image enhancement model of the dynamical saturating nonlinearity based on the total variational regular term.Then,the model is analyzed and extended,and the total variational regular term is replaced with a general regular term to obtain the general form of the model.Finally,the alternating direction multiplier method is used to solve the model,It is decomposed into three interrelated subproblems.The second of these subproblems can be solved as a denoising problem,and the denoising methods include total variational denoising,total generalized total variational denoising,nonlocal total variational denoising,and BM3D denoising,depending on the form of the regular terms in it.The experimental results show that the dynamic saturation nonlinear system image enhancement model based on variation can not only actively improve the brightness and contrast of the image,but also effectively reduce the noise in the image and enhance the detail information of the image.