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Morphological Decomposition Systems with Perfect Reconstruction: From Pyramids to Wavelets

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Space, Structure and Randomness

Part of the book series: Lecture Notes in Statistics ((LNS,volume 183))

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Abstract

Multiresolution methods in signal and image processing are very useful for the following reasons: (i) there is substantial evidence that the human visual system processes visual information in a ‘multiresolution’ fashion; (ii) often, images contain features of physically significant structure at different resolutions; (iii) sensors may provide data of the same source at multiple resolutions; (iv) multiresolution image processing algorithms offer computational advantages and, moreover, appear to be robust.

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Author information

Authors and Affiliations

  1. CWI, P.O. Box 94079 GB, Amsterdam, The Netherlands

    Henk J. A. M. Heijmans

  2. Center for Imaging Science, The Johns Hopkins University, Baltimore, MD, 21218, USA

    John Goutsias

Authors
  1. Henk J. A. M. Heijmans
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  2. John Goutsias
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Editor information

Editors and Affiliations

  1. Centre de Morphologie Mathématique, Ecole des Mines de Paris, 35 rue Saint Honoré, 77305, Fontainebleau, France

    Michel Bilodeau  & Fernand Meyer  & 

  2. Direction des recherches, Ecole des Mines de Paris, 60 Boulevard Saint Michel, 75272, Paris Cedex 06, France

    Michel Schmitt

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Heijmans, H.J.A.M., Goutsias, J. (2005). Morphological Decomposition Systems with Perfect Reconstruction: From Pyramids to Wavelets. In: Bilodeau, M., Meyer, F., Schmitt, M. (eds) Space, Structure and Randomness. Lecture Notes in Statistics, vol 183. Springer, New York, NY. https://doi.org/10.1007/0-387-29115-6_12

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