Patch-Wise Ideal Stopping Time For Anisotropic Diffusion

Data-dependent filtering methods are powerful techniques for image denoising. Beginning with any base procedure (nonlinear filter), repeated applications of the same process can be interpreted as a discrete version of anisotropic diffusion. As such, a natural question is "What is the best stopping time in iterative data-dependent filtering?" This is the general question we address in this paper. To develop our new method, we estimate the mean-squared-error (MSE) in each image patch. This estimate is used to characterize the effectiveness of the iterative filtering process, and its minimization yields the ideal stopping time for the diffusion process.