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Vectorial Features in Pyramidal Image Processing

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Pyramidal Systems for Computer Vision

Part of the book series: NATO ASI Series ((NATO ASI F,volume 25))

Abstract

The notion of pyramidal data structures is useful for segmentation, classification, and representation of images. Ordinarily scalar features are calculated for a selected level of resolution and combined with corresponding features at different levels hierarchically after classification. As a generalization vectorial features are defined. Their components are taken from different levels of Laplacian pyramids and classified by similarity in a vector space which is homogeneous with respect to resolution. These features allow general or quite specific representations of image details.

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References

  1. Burt, P.J.: The Pyramid as a Structure for Efficient Computation. In: Rosenfeld, A. (Editor): Multiresolution Image Processing and Analysis. Springer Berlin Heidelberg New York Tokyo, 1984, pp. 6–35

    Google Scholar 

  2. Crowley, J.L.: A Multiresolution Representation for Shape. In: Rosenfeld, A. (Editor): Multiresolution Image Processing and Analysis, Springer Berlin Heidelberg New York Tokyo, 1984, pp. 169–189

    Google Scholar 

  3. Laws, K.I.: Texture Energy Measures. In: Proc. DARPA Image Understanding Workshop, Los Angeles, 1979, pp. 47–51

    Google Scholar 

  4. Anderson, C.H., Burt, P.J., van der Wal, G.S.: Change Detection and Tracking Using Pyramid Transform Techniques. In: Intelligent Robots and Computer Vision, Proc. SPIE Vol. 579, 1985, pp. 72–78

    Google Scholar 

  5. Hartmann, G.: Erzeugung und Verarbeitung hierarchisch codierter Konturinformationen. VDE-Fachberichte 35, VDE-Verlag, 1983, pp. 378–383

    Google Scholar 

  6. Kronberg, H., Zimmer, H.-G., Neuhoff, V.: A High-Performance 2D Gel Scanner. Clin. Chem. 30, 1984, pp. 2059–2062

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institute for Microelectronics Stuttgart, D-7000, Stuttgart 80, Germany

    H.-G. Zimmer

Authors
  1. H.-G. Zimmer
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Editor information

Editors and Affiliations

  1. Istituto di Informatica e Sistematica, Pavia University, Strada Nuova 106/C, 27100, Pavia, Italy

    Virginio Cantoni

  2. Dipartimento di Matematica, Rome University, Piazzale Aldo Moro 2, 00185, Rome, Italy

    Stefano Levialdi

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© 1986 Springer-Verlag Berlin Heidelberg

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Cite this paper

Zimmer, HG. (1986). Vectorial Features in Pyramidal Image Processing. In: Cantoni, V., Levialdi, S. (eds) Pyramidal Systems for Computer Vision. NATO ASI Series, vol 25. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-82940-6_19

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  • DOI: https://doi.org/10.1007/978-3-642-82940-6_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-82942-0

  • Online ISBN: 978-3-642-82940-6

  • eBook Packages: Springer Book Archive

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