Selection of Optimal Stopping Time for Nonlinear Diffusion Filtering
Pavel Mrazek, CMP Praha, Czech Republic
We present a novel time-selection strategy for iterative image
restoration techniques: the stopping time is chosen so that the
correlation of signal and noise in the filtered image is minimised. The
new method is applicable to any images where the noise to be removed is
uncorrelated with the signal; no other knowledge
(e.g.~the noise variance, training data etc.) is needed. We test the
performance of our time estimation procedure experimentally, and
demonstrate that it yields near-optimal results for a wide range of
noise levels and for various filtering methods.