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