Blind image estimation through fuzzy matching pursuits (Contributo in atti di convegno)

Type
Label
  • Blind image estimation through fuzzy matching pursuits (Contributo in atti di convegno) (literal)
Anno
  • 2001-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/ICIP.2001.958998 (literal)
Alternative label
  • Bruno Aiazzi; Stefano Baronti; Luciano Alparone (2001)
    Blind image estimation through fuzzy matching pursuits
    in IEEE ICIP 2001: 2001 IEEE International Conference on Image Processing, Salonicco, Grecia, 7-10 Ottobre 2001
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Bruno Aiazzi; Stefano Baronti; Luciano Alparone (literal)
Pagina inizio
  • 241 (literal)
Pagina fine
  • 244 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=958998 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Proceedings of ICIP 2001: 2001 IEEE International Conference on Image Processing (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 1 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 4 (literal)
Note
  • ISI Web of Science (WOS) (literal)
  • Google Scholar (literal)
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • \"Nello Carrara\" I.R.O.E. - C.N.R, Via Panciatichi, 64, 50127 Firenze, Italy \"Nello Carrara\" I.R.O.E. - C.N.R, Via Panciatichi, 64, 50127 Firenze, Italy DET, University of Florence, Via S. Marta, 3,50139 Firenze, Italy (literal)
Titolo
  • Blind image estimation through fuzzy matching pursuits (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 0-7803-6725-1 (literal)
Abstract
  • This paper presents an original application of fuzzy logic to restoration of images affected by white noise, possibly nonstationary and/or signal dependent. Space-varying linear MMSE estimation is state as a problem of matching pursuits, in which the estimator is obtained as an expansion in series of a finite number of prototype estimators, fitting the spatial features of the different statistical classes encountered, e.g., edges and textures. Such estimators are calculated in a fuzzy fashion through an automatic training procedure. The space-varying coefficients of the expansion are stated as degrees of fuzzy membership of a pixel to each of the estimators. Besides the fact that neither \"a priori\" knowledge on the noise model is required nor a particular signal model is assumed, a performance comparison high-lights the advantages of the proposed approach. Results on simulated noisy versions of Lenna show a steady SNR improvement of almost 3 dB over Kuan's LLMMSE filtering and over 2 dB over wavelet thresholding, irrespective of noise model and intensity. (literal)
Editore
Prodotto di
Autore CNR
Insieme di parole chiave

Incoming links:


Autore CNR di
Prodotto
Editore di
Insieme di parole chiave di
data.CNR.it