Fuzzy blending of relaxation-labeled predictors for high-performance lossless image compression (Contributo in atti di convegno)

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Label
  • Fuzzy blending of relaxation-labeled predictors for high-performance lossless image compression (Contributo in atti di convegno) (literal)
Anno
  • 2000-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1117/12.382921 (literal)
Alternative label
  • Bruno Aiazzi; Luciano Alparone; Stefano Baronti (2000)
    Fuzzy blending of relaxation-labeled predictors for high-performance lossless image compression
    in SPIE Electronic Imaging 2000: Applications of Artificial Neural Networks in Image Processing V, San Jose, CA, USA, 25-28 Gennaio 2000
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Bruno Aiazzi; Luciano Alparone; Stefano Baronti (literal)
Pagina inizio
  • 41 (literal)
Pagina fine
  • 49 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://spiedigitallibrary.org/proceedings/resource/2/psisdg/3962/1/41_1?isAuthorized=no (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Proceedings of SPIE Electronic Imaging 2000: Applications of Artificial Neural Networks in Image Processing V (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 3962 (literal)
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  • 3962 (literal)
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  • 9 (literal)
Note
  • Google Scholar (literal)
  • ISI Web of Science (WOS) (literal)
  • Scopu (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 di Santa Marta, 3, I-50139 Firenze, Italy \"Nello Carrara\" Research Institute on Electromagnetic Waves IROE-CNR, Via Panciatichi, 64, I-50127 Firenze, Italy (literal)
Titolo
  • Fuzzy blending of relaxation-labeled predictors for high-performance lossless image compression (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 0-8194-3580-5 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
  • N. M. Nasrabadi; A. K. Katsaggelos (literal)
Abstract
  • This paper deals with application of fuzzy and neural techniques to the reversible intraframe compression of grayscale images. With reference to a spatial DPCM scheme, prediction may be accomplished in a space varying fashion following two main strategies: adaptive, i.e., with predictors recalculated at each pixel position, and classified, in which image blocks, or pixels are preliminarily labeled into a number of statistical classes, for which minimum MSE predictors are calculated. Here, a trade off between the above two strategies is proposed, which relies on a space-varying linear-regression prediction obtained through fuzzy techniques, and is followed by context based statistical modeling of prediction errors, to enhance entropy coding. A thorough comparison with the most advanced methods in the literature, as well as an investigation of performance trends to work parameters, highlight the advantages of the fuzzy approach. (literal)
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