http://www.cnr.it/ontology/cnr/individuo/prodotto/ID44392
Non-stationary t-distribution prior for image source separation from blurred observations (Contributo in atti di convegno)
- Type
- Label
- Non-stationary t-distribution prior for image source separation from blurred observations (Contributo in atti di convegno) (literal)
- Anno
- 2010-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1007/978-3-642-15995-4_63 (literal)
- Alternative label
Kayabol K., Kuruoglu E. E. (2010)
Non-stationary t-distribution prior for image source separation from blurred observations
in LVA/ICA 2010 - Latent Variable Analysis and Signal Separation. 9th International Conference, St. Malo, France, 27-30 September 2010
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Kayabol K., Kuruoglu E. E. (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://www.springerlink.com/content/r85885j6t37n3642/ (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
- In: LVA/ICA 2010 - Latent Variable Analysis and Signal Separation. 9th International Conference (St. Malo, France, 27-30 September 2010). Proceedings, pp. 506 - 513. Vincent Vigneron, Vicente Zarzoso, Eric Moreau, Rémi Gribonval, Emmanuel Vincent (eds.). (Lecture Notes in Computer Science, vol. 6365). Springer, 2010. (literal)
- Note
- Scopu (literal)
- ISI Web of Science (WOS) (literal)
- PuMa (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy (literal)
- Titolo
- Non-stationary t-distribution prior for image source separation from blurred observations (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- 978-3-642-15995-4 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
- Vincent Vigneron, Vicente Zarzoso, Eric Moreau, Rémi Gribonval, Emmanuel Vincent (literal)
- Abstract
- We propose a non-stationary spatial image model for blind image separation problem. Our model is defined on first order image differentials. We model the image differentials using t-distribution with space varying scale parameters. This prior image model has been used in the Bayesian formulation and the image source are estimated using a Langevin sampler method. We have tested the proposed model on astrophysical image mixtures and obtained better results regarding to stationary model. (literal)
- Prodotto di
- Autore CNR
- Insieme di parole chiave
Incoming links:
- Prodotto
- Autore CNR di
- Insieme di parole chiave di