An adaptive diffusion denoising iterations approach based on the local minimum correlation coefficient
Xinping Chen · Jiguang zazhi · 2011
In order to overcome the lack of fixed number of the iterations of classical Perona-Malik anisotropic diffusion denoising model,a novel adaptive algorithm to determine the number of iterations is proposed in this paper.It auto-controls the number of iterations of the typical Perona-Malik model according to the minimum local correlation coefficient between denoised image and noise of image itself.Experiment results have shown that the proposed algorithm is better than that of the rigid iterations either in the noise removing or in the edge preserving,and it has a certian generality in the application.