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GET: The connection between monogenic scale-space and Gaussian derivatives
Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.
2005 (English)In: Scale Space and PDE Methods in Computer Vision, 2005, Vol. 3459, 192-203 p.Conference paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
2005. Vol. 3459, 192-203 p.
, Lecture Notes in Computer Science, 3459
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-48204OAI: diva2:269100
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2009-11-13

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Felsberg, Michael
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The Institute of TechnologyComputer Vision
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