Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/49714
Título: A Riemannian approach to anisotropic filtering of tensor fields
Autores/as: Castaño-Moraga, C. A.
Lenglet, C.
Deriche, R.
Ruiz-Alzola, J. 
Clasificación UNESCO: 3325 Tecnología de las telecomunicaciones
Palabras clave: Signal processing
Tensors
Fecha de publicación: 2007
Editor/a: 0165-1684
Publicación seriada: Signal Processing 
Resumen: Tensors are nowadays an increasing research domain in different areas, especially in image processing, motivated for example by diffusion tensor magnetic resonance imaging (DT-MRI). Up to now, algorithms and tools developed to deal with tensors were founded on the assumption of a matrix vector space with the constraint of remaining symmetric positive definite matrices. On the contrary, our approach is grounded on the theoretically well-founded differential geometrical properties of the space of multivariate normal distributions, where it is possible to define an affine-invariant Riemannian metric and express statistics on the manifold of symmetric positive definite matrices. In this paper, we focus on the contribution of these tools to the anisotropic filtering and regularization of tensor fields. To validate our approach we present promising results on both synthetic and real DT-MRI data.
URI: http://hdl.handle.net/10553/49714
ISSN: 0165-1684
DOI: 10.1016/j.sigpro.2006.02.049
Fuente: Signal Processing[ISSN 0165-1684],v. 87, p. 263-276
Colección:Artículos
Vista completa

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.