Systematic Sampling in Image-Synthesis

  • Mateu Sbert
  • Jaume Rigau
  • Miquel Feixas
  • Laszlo Neumann
Conference paper

DOI: 10.1007/11751540_48

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3980)
Cite this paper as:
Sbert M., Rigau J., Feixas M., Neumann L. (2006) Systematic Sampling in Image-Synthesis. In: Gavrilova M. et al. (eds) Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3980. Springer, Berlin, Heidelberg

Abstract

In this paper we investigate systematic sampling in the image- synthesis context. Systematic sampling has been widely used in stereology to improve the efficiency of different probes in experimental design. These designs are theoretically based on estimators of 1-dimensional and 2-dimensional integrals. For the particular case of the characteristic function, the variance of these estimators has been shown to be asymptotically N − − 3/2, which improves on the O(N − − 1) behaviour of independent estimators using uniform sampling. Thus, when no a priori knowledge of the integrand function is available, like in several image synthesis techniques, systematic sampling efficiently reduces the computational cost.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mateu Sbert
    • 1
  • Jaume Rigau
    • 1
  • Miquel Feixas
    • 1
  • Laszlo Neumann
    • 1
  1. 1.Institut d’Informatica i AplicacionsUniversitat de GironaSpain

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