Wavelet and pyramid filtering of signal-dependent noise (Contributo in atti di convegno)

Type
Label
  • Wavelet and pyramid filtering of signal-dependent noise (Contributo in atti di convegno) (literal)
Anno
  • 2000-01-01T00:00:00+01:00 (literal)
Alternative label
  • Bruno Aiazzi; Luciano Alparone; Stefano Baronti (2000)
    Wavelet and pyramid filtering of signal-dependent noise
    in Tenth European Signal Processing Conference (EUSIPCO 2000), Tampere, Finlandia, 4-8 Settembre 2000
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Bruno Aiazzi; Luciano Alparone; Stefano Baronti (literal)
Pagina inizio
  • 2365 (literal)
Pagina fine
  • 2368 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.eurasip.org/Proceedings/Eusipco/Eusipco2000/SESSIONS/FRIPM/OR2/CR1686.PDF (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Signal Processing X: Theories and Applications; Proceedings of EUSIPCO 2000, 10th European Signal Processing Conference (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 4 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 4 (literal)
Note
  • Google Scholar (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • \"Nello Carrara\" Research Institute on Electromagnetic Waves IROE-CNR, Via Panciatichi, 64, I-50127 Firenze, Italy Department of Electronics and Telecommunications, University of Florence, Via S. Marta, 3, I-50139 Firenze, Italy \"Nello Carrara\" Research Institute on Electromagnetic Waves IROE-CNR, Via Panciatichi, 64, I-50127 Firenze, Italy (literal)
Titolo
  • Wavelet and pyramid filtering of signal-dependent noise (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 952-15-0447-1 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
  • M. Gabbouj; P. Kuosmanen (literal)
Abstract
  • In this paper, after reviewing a general model to deal with signal-dependent image noise, the well known Local Linear Minimum Mean Squared Error (LLMMSE) Kuan's filter is derived for the most general case. Signal-dependent noise filtering is approached in a multiresolution framework either by LLMMSE processing ratios of combinations of low-pass images, which are tailored to the noise model in order to mitigate its signal-dependence, or by thresholding a normalized non-redundant wavelet transform designed to yield signal-independent noisy coefficients as well. Experimental results demonstrate that the Laplacian pyramid approach largely outperform LLMMSE filtering on a unique scale and is still superior to wavelet de-noising by thresholding. (literal)
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