Guedj, B;
Rengot, J;
(2020)
Non-linear Aggregation of Filters to Improve Image Denoising.
In: Arai, K and Kapoor, S and Bhatia, R, (eds.)
SAI 2020: Intelligent Computing.
(pp. pp. 314-327).
Springer: London, UK.
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Abstract
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.
| Type: | Proceedings paper |
|---|---|
| Title: | Non-linear Aggregation of Filters to Improve Image Denoising. |
| Event: | Science and Information Conference |
| ISBN-13: | 978-3-030-52245-2 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://doi.org/10.1007/978-3-030-52246-9_22 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | image denoising, statistical aggregation, ensemble methods, collaborative filtering |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10107086 |
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