scholarly journals Estimation of Non-Cartesian Local Structure Tensor Fields

Author(s):  
Björn Svensson ◽  
Anders Brun ◽  
Mats Andersson ◽  
Hans Knutsson
2020 ◽  
Vol 35 (1) ◽  
pp. 121
Author(s):  
Adara-Monica Blaga

We give the expressions of the virtual and the structure tensor fields of an almost paracontact metric structure. We also introducethe notion of paracontactly geodesic transformation and prove thatthe structure tensor field is invariant under conformal andparacontactly geodesic transformations. For the particular case of para-Kenmotsu structure, we give a necessary and sufficient condition for a conformal transformation to map it to an $\alpha$-para-Kenmotsu structure and show that a para-Kenmotsu manifold admits no nontrivial paracontactly geodesic transformation of the metric. In the conformal case, the virtual tensor field is invariant.  


Author(s):  
E. Suárez-Santana ◽  
M. A. Rodriguez-Florido ◽  
C. Castaño-Moraga ◽  
C.-F. Westin ◽  
J. Ruiz-Alzola

2010 ◽  
Author(s):  
Andinet Enquobahrie ◽  
Hua Yang ◽  
Stephen Aylward

This paper describes implementation of local structure tensor and anisotropic enhancement diffusion filters using the Insight Toolkit. The anisotropic diffusion filters are implemented using ITK’s finite difference solver framework. The filters are used to implement the 3D edge-enhancing diffusion ( EED), coherence-enhancing diffusion (CED) and hybrid diffusion with continuous switch(HDCS) noise filtering algorithms described in Mendrik et al[1].The most up-to-date version of the code presented in this paper is distributed with the TubeTK project: http://public.kitware.com/Wiki/TubeTK


2012 ◽  
Author(s):  
Sergio Vera ◽  
Debora Gil ◽  
Antonio López ◽  
Miguel A. González

This document describes the implementation using the Insight Toolkit of an algorithm for detecting creases (ridges and valleys) in N-dimensional images, based on the Local Structure Tensor of the image. In addition to the filter used to calculate the creaseness image, a filter for the computation of the structure tensor is also included in this submission.


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