Context Modeling for Near-Lossless Image Coding (Articolo in rivista)

Type
Label
  • Context Modeling for Near-Lossless Image Coding (Articolo in rivista) (literal)
Anno
  • 2002-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/97.995822 (literal)
Alternative label
  • Bruno Aiazzi; Luciano Alparone; Stefano Baronti (2002)
    Context Modeling for Near-Lossless Image Coding
    in IEEE signal processing letters; IEEE-Institute Of Electrical And Electronics Engineers Inc., Piscataway (Stati Uniti d'America)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Bruno Aiazzi; Luciano Alparone; Stefano Baronti (literal)
Pagina inizio
  • 77 (literal)
Pagina fine
  • 80 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=995822 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 9 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 4 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 3 (literal)
Note
  • Scopu (literal)
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Nello Carrara Research Institute on Electromagnetic Waves (IROE), National Research Council (CNR), I-50127 Florence, Italy Department of Electronics and Telecommunications, University of Florence, I-50139 Florence, Italy Nello Carrara Research Institute on Electromagnetic Waves (IROE), National Research Council (CNR), I-50127 Florence, Italy (literal)
Titolo
  • Context Modeling for Near-Lossless Image Coding (literal)
Abstract
  • This letter describes a context-based entropy coding suitable for any causal spatial differential pulse code modulation (DPCM) scheme performing lossless or near-lossless image coding. The proposed method is based on partitioning of prediction errors into homogeneous classes before arithmetic coding. A context function is measured on prediction errors lying within a two-dimensional (2-D) causal neighbourhood, comprising the prediction support of the current pixel, as the root mean square (RMS) of residuals weighted by the reciprocal of their Euclidean distances. Its effectiveness is demonstrated in comparative experiments concerning both lossless and near-lossless coding. The proposed context coding/decoding is strictly real-time. (literal)
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