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On the Representation of Visual Information

  • Mario Ferraro
  • Giuseppe Boccignone
  • Terry Caelli
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2059)

Abstract

Loss of information in images undergoing fine-to-coarse image transformations is analized by using an approach based on the theory of irreversible transformations. It is shown that entropy variation along scales can be used to characterize basic, low-level information and to gauge essential perceptual components of the image, such as shape and texture. The use of isotropic and anisotropic fine-to-coarse transformations of grey level images is discussed, and an extension of the approach to multi-valued images is proposed, where cross-interactions between the different colour channels are allowed.

Keywords

Visual Information Color Image Entropy Production Color Channel Isotropic Case 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Mario Ferraro
    • 1
  • Giuseppe Boccignone
    • 2
  • Terry Caelli
    • 3
  1. 1.Dipartimento di Fisica SperimentaleUniversità di Torino and INFMItaly
  2. 2.Dipartimento di Ingegneria dell’Informazione e Ingegneria ElettricaUniversità di Salerno and INFMItaly
  3. 3.Department of Computing ScienceThe University of AlbertaEdmontonCanada

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