Research On Sar Image Denoising Based On Variation And Partial Differential Equations

Image processing has a wide range of applications in real life.Image denoising is one of the important research contents of image processing.With the development of relevant techniques about denoise,the research on the method about the removal of Gamma noise in SAR image has also made great process.The quality of the image is affected by noise in the image,such as the lost of details of image or blurred,which will bring great challenges for subsequent image processing.The variation based on partial differential equation has become one of the hotspots in the field of image denoising due to its advantages.This paper is concerned with the SAR image denoising methods based on variation and partial differential equations.The main research contents and innovations are as follows:(1) Combined with the JY model, the adaptive model about removing gamma noise is given.Then, a fast numerical algorithm for solving the model is developed by using the IADMM algorithm.Finally, the numerical simulation results show the effectiveness and feasibility of the algorithm.(2) According to the shortcomings of the existing model, the denoising model based on partial differential equation is given by introducing new regularization.Then, a fast numerical algorithm for solving the model is developed by using the AMA algorithm.Finally, the numerical simulation results show the effectiveness and feasibility of the algorithm.(3) Based on the HNW model and the LLT model, the adaptive denoising model is proposed based on hybrid-order partial differential equation.Then using the AMA algorithm, the fast algorithm is developed for solving the model.Finally, the numerical simulation results show the effectiveness and feasibility of the algorithm.