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Scale Adaptive Filtering Derived from the Laplace Equation

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Pattern Recognition (DAGM 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2191))

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Abstract

In this paper, we present a new approach to scale-space which is derived from the 3D Laplace equation instead of the heat equation. The resulting lowpass and bandpass filters are discussed and they are related to the monogenic signal. As an application, we present a scale adaptive filtering which is used for denoising images. The adaptivity is based on the local energy of spherical quadrature filters and can also be used for sparse representation of images.

This work has been supported by German National Merit Foundation and by DFG Graduiertenkolleg No. 357 (M. Felsberg) and by DFG Grant So-320-2-2 (G.Sommer).

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Authors
  1. Michael Felsberg
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  2. Gerald Sommer
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Editor information

Editors and Affiliations

  1. Chair of Image Understanding and Knowledge Based Systems, Technical University Munich, Orleansstr. 34, 81667, Munich, Germany

    Bernd Radig  & Stefan Florczyk  & 

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Felsberg, M., Sommer, G. (2001). Scale Adaptive Filtering Derived from the Laplace Equation. In: Radig, B., Florczyk, S. (eds) Pattern Recognition. DAGM 2001. Lecture Notes in Computer Science, vol 2191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45404-7_17

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  • DOI: https://doi.org/10.1007/3-540-45404-7_17

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42596-0

  • Online ISBN: 978-3-540-45404-5

  • eBook Packages: Springer Book Archive

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