Section: New Results

Axis 2: Non-linear aggregation of filters to improve image denoising

Participant: Benjamin Guedj

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.

Joint work with Juliette Rengot (Ecole des Ponts).

This work has been accepted at the Computing Conference 2020 (July 2020, London, UK) and will be included in the proceedings. Published: [33]