Nonparametric Supervised Image Segmentation by Energy Minimization using Wavelets

  • Jacques Istas
Part of the Lecture Notes in Statistics book series (LNS, volume 103)

Abstract

Energy models, like the Mumford and Shah model, have been introduced for segmenting images. The boundary, defined as the minimum of the energy, is projected onto a wavelet basis. We assume a white noise model on the observed image. The aim of this paper is to study the asymptotic behavior of non-parametric estimators of the boundary when the number of pixels grows to infinity.

Keywords

Convolution 

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Copyright information

© Springer-Verlag New York 1995

Authors and Affiliations

  • Jacques Istas
    • 1
  1. 1.Laboratoire de BiometriéDomaine de Vilvert, I.N.R.A.Jouy-en-JosasFrance

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