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Pyramid Transform and Scale-Space Analysis in Image Analysis

  • Yoshihiko Mochizuki
  • Atsushi Imiya
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Mobile Robot Gaussian Kernel Coarse Grid Angle Error Spherical Image 
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 2012

Authors and Affiliations

  • Yoshihiko Mochizuki
    • 1
  • Atsushi Imiya
    • 2
  1. 1.Faculty of Science and EngineeringWaseda University, JapanTokyoJapan
  2. 2.Institute of Media and Information TechnologyChiba University, JapanChibaJapan

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