GET: The Connection Between Monogenic Scale-Space and Gaussian Derivatives

Felsberg, M., Köthe, U.
Scale Space 2005
Scale Space and PDE Mathods in Computer Vision
Volume 3459, Pages 192-203
2005

Abstract

In this paper we propose a new operator which combines advantages of monogenic scale-space and Gaussian scale-space, of the monogenic signal and the structure tensor. The gradient energy tensor (GET) defined in this paper is based on Gaussian derivatives up to third order using different scales. These filters are commonly available, separable, and have an optimal uncertainty. The response of this new operator can be used like the monogenic signal to estimate the local amplitude, the local phase, and the local orientation of an image, but it also allows to measure the coherence of image regions as in the case of the structure tensor. Both theoretically and in experiments the new approach compares favourably with existing methods.

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Bibtex entry

@inproceedings{fk05,
	Author = {Felsberg, M. and K{\"o}the, U.},
	Booktitle = {Scale Space and PDE Mathods in Computer Vision},
	Editor = {Kimmel, R. and Sochen, N. and Weickert, J.},
	Pages = {192--203},
	Publisher = {Springer},
	Series = {LNCS},
	Title = {GET: The Connection Between Monogenic Scale-Space and
                 Gaussian Derivatives},
	Volume = {3459},
	Year = {2005}
}