Image Denosing Methods Based On Partial Differential Equations And Application In Biomedical

With the popularization of various kinds of digital instruments and products, digital image processing has become a new crossing field of mathematics method and computer technique.Image de-noising is an important component part of digital image processing technology. Biomedical is a field aaplying digital image processing. In medical science, image processing is widely applied to basic subjects and clinical applications.This paper focuses on image processing based on partial differential equations method and its application in biological medicine.The main contents may be summarized as the following:This paper introduces research history and background of image de-noising based on partial differenial equations, and analysis several image denoising models based on partial differential equations in their own advantages and disadvantages. We improve the model based on nonlinear mixed anisotropic diffusion equation for its shortcomings, And the same improved method was applied to multiplicative noise denoising.We introduce a model to denoise an image corrupted by Poisson noise and improve it. Considering isolated niose,so firstly image is improved by gaussian filter. But because smoothing parameter is a fixed number, image features are blured. So in this paper the smoothing parameter is a function of the time. As removing image noise we can keep image features.At last, we apply these models in biomedical image and remove image noise. The good effect is obtained and new thinking and method are proposed for research on Biomedical image processing.