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Pyramid Transform and Scale-Space Analysis in Image Analysis

  • Conference paper
Outdoor and Large-Scale Real-World Scene Analysis

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7474))

Abstract

The pyramid transform compresses images while preserving global features such as edges and segments. The pyramid transform is efficiently used in optical flow computation starting from planar images captured by pinhole camera systems, since the propagation of features from coarse sampling to fine sampling allows the computation of both large displacements in low-resolution images sampled by a coarse grid and small displacements in high-resolution images sampled by a fine grid.

The image pyramid transform involves the resizing of an image by downsampling after convolution with the Gaussian kernel. Since the convolution with the Gaussian kernel for smoothing is derived as the solution of a linear diffusion equation, the pyramid transform is performed by applying a downsampling operation to the solution of the linear diffusion equation.

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Author information

Authors and Affiliations

  1. Faculty of Science and Engineering, Waseda University, Japan, Okubo 3-4-1, Shinjuku-ku, Tokyo, 169-8555, Japan

    Yoshihiko Mochizuki

  2. Institute of Media and Information Technology, Chiba University, Japan, Yayoicho 1-33, Inage-ku, Chiba, 263-8522, Japan

    Atsushi Imiya

Authors
  1. Yoshihiko Mochizuki
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  2. Atsushi Imiya
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Editor information

Editors and Affiliations

  1. College of Computing Building, Georgia Institute of Technology, 801 Atlantic Drive, 30332-0280, Atlanta, GA, USA

    Frank Dellaert

  2. Department of Computer Science, University of North Carolina at Chapel Hill, Brooks Computer Science Building, CB#3175, 27599, Chapel Hill, NC, USA

    Jan-Michael Frahm

  3. CVG - Institute of Visual Computing, Department of Computer Science, ETH Zurich, CNB G105, Universitaetstrasse 6, 8092, Zurich, Switzerland

    Marc Pollefeys

  4. Institute for Information Processing (TNT), Leibniz Universität, Appelstr. 9A, 30167, Hannover, Germany

    Laura Leal-Taixé

  5. Institute for Information Processing (TNT), Leibniz Universität, Appelstr. 9A, 30167, Hannover, Germany

    Bodo Rosenhahn

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Mochizuki, Y., Imiya, A. (2012). Pyramid Transform and Scale-Space Analysis in Image Analysis. In: Dellaert, F., Frahm, JM., Pollefeys, M., Leal-Taixé, L., Rosenhahn, B. (eds) Outdoor and Large-Scale Real-World Scene Analysis. Lecture Notes in Computer Science, vol 7474. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34091-8_4

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  • DOI: https://doi.org/10.1007/978-3-642-34091-8_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34090-1

  • Online ISBN: 978-3-642-34091-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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