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Diffusion-based spatial priors for imaging
We describe a Bayesian scheme to analyze images, which uses spatial priors encoded by a diffusion kernel, based on a weighted graph Laplacian. This provides a general framework to formulate a spatial model, whose parameters can be optimized. The application we have in mind is a spatiotemporal model...
| Autores principales: | , , , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
Academic Press
2007
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2643839/ https://www.ncbi.nlm.nih.gov/pubmed/17869542 http://dx.doi.org/10.1016/j.neuroimage.2007.07.032 |