Adaptive regularization of the NL-means for video denoising
| hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
| hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
| dc.contributor.author | SUTOUR, Camille | |
| hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
| dc.contributor.author | AUJOL, Jean-François | |
| hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
| dc.contributor.author | DELEDALLE, Charles-Alban | |
| hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
| dc.contributor.author | DOMENGER, Jean-Philippe | |
| dc.date.accessioned | 2024-04-04T03:22:08Z | |
| dc.date.available | 2024-04-04T03:22:08Z | |
| dc.date.created | 2014-01-20 | |
| dc.date.issued | 2014-10-27 | |
| dc.date.conference | 2014-10-27 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/194727 | |
| dc.description.abstractEn | We derive a denoising method based on an adaptive regularization of the non-local means. The NL-means reduce noise by using the redundancy in natural images. They compute a weighted average of pixels whose surroundings are close. This method performs well but it suffers from residual noise on singular structures. We use the weights computed in the NL-means as a measure of performance of the denoising process. These weights balance the data-fidelity term in an adapted ROF model, in order to locally perform adaptive TV regularization. Besides, this model can be adapted to different noise statistics and a fast resolution can be computed in the general case of the exponential family. We adapt this model to video denoising by using spatio-temporal patches. Compared to spatial patches, they offer better temporal stability, while the adaptive TV regularization corrects the residual noise observed around moving structures. | |
| dc.language.iso | en | |
| dc.source.title | IEEE International Conference on Image Processing 2014 | |
| dc.title.en | Adaptive regularization of the NL-means for video denoising | |
| dc.type | Communication dans un congrès | |
| dc.subject.hal | Informatique [cs]/Traitement des images | |
| bordeaux.page | 5 p. | |
| bordeaux.hal.laboratories | Institut de Mathématiques de Bordeaux (IMB) - UMR 5251 | * |
| bordeaux.institution | Université de Bordeaux | |
| bordeaux.institution | Bordeaux INP | |
| bordeaux.institution | CNRS | |
| bordeaux.conference.title | IEEE International Conference on Image Processing 2014 | |
| bordeaux.country | FR | |
| bordeaux.title.proceeding | IEEE International Conference on Image Processing 2014 | |
| bordeaux.conference.city | Paris | |
| bordeaux.peerReviewed | oui | |
| hal.identifier | hal-01016610 | |
| hal.version | 1 | |
| hal.invited | non | |
| hal.proceedings | oui | |
| hal.conference.end | 2014-10-30 | |
| hal.popular | non | |
| hal.audience | Internationale | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-01016610v1 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.btitle=IEEE%20International%20Conference%20on%20Image%20Processing%202014&rft.date=2014-10-27&rft.spage=5%20p.&rft.epage=5%20p.&rft.au=SUTOUR,%20Camille&AUJOL,%20Jean-Fran%C3%A7ois&DELEDALLE,%20Charles-Alban&DOMENGER,%20Jean-Philippe&rft.genre=unknown |
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