http://www.cnr.it/ontology/cnr/individuo/prodotto/ID186723
Lossless image compression based on an enhanced fuzzy regression prediction (Contributo in atti di convegno)
- Type
- Label
- Lossless image compression based on an enhanced fuzzy regression prediction (Contributo in atti di convegno) (literal)
- Anno
- 1999-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1109/ICIP.1999.821646 (literal)
- Alternative label
Bruno Aiazzi; Stefano Baronti; Luciano Alparone (1999)
Lossless image compression based on an enhanced fuzzy regression prediction
in IEEE ICIP99, 1999 IEEE International Conference on Image Processing, Kobe, Giappone, 24-28 Ottobre 1999
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Bruno Aiazzi; Stefano Baronti; Luciano Alparone (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=821646 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- Proceedings of IEEE ICIP99: 1999 IEEE International Conference on Image Processing (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Note
- Scopu (literal)
- Google Scholar (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
Dept. Electron. Engin., Univ. Florence, Via S. Marta, 3, 50139 Firenze, Italy (literal)
- Titolo
- Lossless image compression based on an enhanced fuzzy regression prediction (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- Abstract
- An effective method for lossless image compression is presented. It relies on a classified linear-regression prediction obtained through fuzzy techniques, followed by context-based modeling of the outcome prediction errors, to enhance entropy coding. The present scheme is a reworking of the fuzzy encoder presented at ICIP'98 (FDC). Now, predictors, instead of pixel intensity patterns, are fuzzy-clustered to find out optimized MMSE prediction classes, and a novel membership function measuring the fitness of prediction is adopted. Size and shape of causal neighborhoods supporting prediction, as well as number of predictors to be blended, may be chosen by user and settle the tradeoff between coding performances and computational costs. The encoder exhibits impressive performances, thanks to the skill of predictors in fitting data patterns as well as to context modeling. (literal)
- Editore
- Prodotto di
- Autore CNR
- Insieme di parole chiave
Incoming links:
- Autore CNR di
- Prodotto
- Editore di
- Insieme di parole chiave di