  We introduce a novel aggregation method to efficiently perform image
denoising. Preliminary filters are aggregated in a non-linear fashion, using a
new metric of pixel proximity based on how the pool of filters reaches a
consensus. We provide a theoretical bound to support our aggregation scheme,
its numerical performance is illustrated and we show that the aggregate
significantly outperforms each of the preliminary filters.
