Study On Algorithm Of Image Denoising Based On Partial Differential Equation

Based on Partial differential Equation (PDE, Partial Differetial Equation) methodhas significant effect on image processing techniques in various kinds of methods. Onthe one hand, it is higher than the accuracy of the traditional linear methods in dealingwith image; on the other hand, this method is able to deal directly with some imagecharacteristics so that to establish variety mathematical model easily. It is a good imagedenoising technique to eliminate noise and protect edge, becouse it is a kind of adaptivedenoising technology and can choose smooth degree according to the strength of theimage area feature.This paper analyzes the research background, basic principle and developmentprocess of image denoising algorithm based on PDE, and expounds the export, designthinking and the numerical implementation process of image denoising algorithm model.This paper mainly includes the following contents.The paper firstly introduces the research background and significance of topicselection, then expounds the development history and the research status of imagedenoising algorithm based on PDE, and gives the main research content and chapterarrangement of this article. Next, the paper introduces the concepts and other basicknowledge related to image denoising, and the traditional evolution based on PDEdenoising model development has carried on the detailed introduction.Chapter3and4is the core of the thesis. We improved an adaptive variationaldenoising algorithm model first based on the traditional total variational denoisingmodel and by changing the regularization parameter and loyalty parameter, and thensimulate and analyse the algorithm in detail. In subsequent papers, we improved afourth order PDE denoising method in view of the traditional second order and fourthorder equation. This method can overcome the block effects caused by second orderpartial differential equations, and eliminate flash point and keep the image details suchas edge, texture lines, so as to achieve better image quality and visual effect on denoisedimage. In addition, the application examples of denoising algorithm in the medicaldiagnosis and mine monitoring is respectively given in chapter3and4of this thesis.