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Binomial Convolutions and Derivatives Estimation from Noisy Discretizations

  • Rémy Malgouyres
  • Florent Brunet
  • Sébastien Fourey
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4992)

Abstract

We present a new method to estimate derivatives of digitized functions. Even with noisy data, this approach is convergent and can be computed by using only the arithmetic operations. Moreover, higher order derivatives can also be estimated. To deal with parametrized curves, we introduce a new notion which solves the problem of correspondence between the parametrization of a continuous curve and the pixels numbering of a discrete object.

Keywords

Parametrized Curve High Order Derivative Discretization Step Discrete Function Pixel Numbering 
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 2008

Authors and Affiliations

  • Rémy Malgouyres
    • 1
  • Florent Brunet
    • 1
  • Sébastien Fourey
    • 2
  1. 1.LAIC, IUT Dépt InformatiqueUniv. Clermont 1AubièreFrance
  2. 2.GREYC Image – ENSICAENCaen CEDEXFrance

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