Abstract
A wavelet transform of a function is, roughly speaking, a description of this function across a range of scales. We use the technique of wavelet transforms to detect discontinuities in the n-th derivative of a function of one variable.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
T. Poggio, H. Voorhes and A. Yuille : ‘A regularized solution to edge detection’ ; Massachusetts Institute of Technology, Artificial Intelligence Laboratory. A.I. Memo 833 (1985)
D. Marr. Vision. A computational investigation into the human representation and processing of visual information:’ W.H. Freeman and Co, San Francisco 1982.
Y. Meyer : ‘Principe d’incertitutde, bases hilbertiennes et algèbres d’opérateurs’ : Séminaire Bourbaki, 1985–86, n° 662.
A. Grossmann and J. Morlet : ‘Decomposition of Hardy functions into square integrable functions of constant shape’ : SIAM J. Math. Anal. 15, 4(1984).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1988 D. Reidel Publishing Company
About this chapter
Cite this chapter
Grossmann, A. (1988). Wavelet Transforms and Edge Detection. In: Albeverio, S., Blanchard, P., Hazewinkel, M., Streit, L. (eds) Stochastic Processes in Physics and Engineering. Mathematics and Its Applications, vol 42. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-2893-0_7
Download citation
DOI: https://doi.org/10.1007/978-94-009-2893-0_7
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-7803-0
Online ISBN: 978-94-009-2893-0
eBook Packages: Springer Book Archive