BookSection
incollection
brunet2008dgci
Binomial Convolutions and Derivatives Estimation from Noisy Discretizations
2008
10.1007/978-3-540-79126-3_33
Malgouyres
Rémy
Brunet
Florent
Fourey
Sébastien
Coeurjolly
David
Sivignon
Isabelle
Tougne
Laure
Dupont
Florent
370-379
4992
Springer Berlin / Heidelberg
Discrete Geometry for Computer Imagery
Lecture Notes in Computer Science
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.
Univ. Clermont 1 LAIC, IUT Dépt Informatique BP 86 F-63172 Aubière France