Non-linear aggregation of filters to improve image denoising
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 1 Apr 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 1.
1 paper.