A robust method for parameter estimation of signal-dependent noise models in digital images (Contributo in atti di convegno)

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  • A robust method for parameter estimation of signal-dependent noise models in digital images (Contributo in atti di convegno) (literal)
Anno
  • 1997-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/ICDSP.1997.628421 (literal)
Alternative label
  • B. Aiazzi; L. Alparone; S. Baronti (1997)
    A robust method for parameter estimation of signal-dependent noise models in digital images
    in DSP 97: 1997 13th International Conference on Digital Signal Processing, Santorini, Grecia, 2-4 Luglio 1997
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • B. Aiazzi; L. Alparone; S. Baronti (literal)
Pagina inizio
  • 601 (literal)
Pagina fine
  • 604 (literal)
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  • http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=628421 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Proceedings of IEEE DSP '97: 1997 13th International Conference on Digital Signal Processing (literal)
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  • 2 (literal)
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  • 4 (literal)
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  • ISI Web of Science (WOS) (literal)
  • Scopu (literal)
  • 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 Electronic Engineering, 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
  • A robust method for parameter estimation of signal-dependent noise models in digital images (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 0-7803-4137-6 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
  • University of Patras, Institution of Electrical Engineers (literal)
Abstract
  • In this paper a class of signal-dependent noise models is discussed, with reference to the cases of film-grain and speckle noise, which are commonly encountered in image processing applications. The model is uniquely defined by the variance of the zero-mean random noise (independent of the signal) and by the gamma exponent which rules the dependence with the signal. A robust procedure for measuring such parameters directly from the noisy images is presented. First, the gamma coefficient is estimated from at least three homogeneous non-textured regions. Then, the noise variance is determined as the mode of the histogram of the ratio between the local variance, and the local mean raised to twice the gamma. Computer simulations show the high accuracy of the results. (literal)
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