Abstract
This paper deals with the parameter choice for the NL-Means algorithm.
Starting with basic computations on toy models, we study the bias-variance
trade-off of this filter using a simple notion of regularity in the
patch space. We show that this regularity is necessarily local and
so should be the parameters of the filter. Relying on Stein's Unbiased
Risk Estimate, we then propose a way to locally set these parameters,
and we compare this method with the Non-Local Means with optimal
global parameter.
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