Estimating the joint statistics of images using nonparametric windows with application to registration using mutual information.
IEEE Trans Pattern Anal Mach Intell
; 30(10): 1841-57, 2008 Oct.
Article
en En
| MEDLINE
| ID: mdl-18703835
Recently, the Nonparametric (NP) Windows has been proposed to estimate the statistics of real 1D and 2D signals. NP Windows is accurate, because it is equivalent to sampling images at a high (infinite) resolution for an assumed interpolation model. This paper extends the proposed approach to consider joint distributions of image-pairs. Second, Green's Theorem is used to simplify the previous NP Windows algorithm. Finally, a resolution-aware NP Windows algorithm is proposed to improve robustness to relative scaling between an image pair. Comparative testing of 2D image registration was performed using translation-only and affine transformations. Although more expensive than other methods, NP Windows frequently demonstrated superior performance for bias (distance between ground truth and global maximum) and frequency of convergence. Unlike other methods, the number of samples and the number of bins have little effect on NP Windows and the prior selection of a kernel is not required.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Reconocimiento de Normas Patrones Automatizadas
/
Inteligencia Artificial
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Interpretación de Imagen Asistida por Computador
/
Aumento de la Imagen
/
Técnica de Sustracción
/
Modelos Teóricos
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Revista:
IEEE Trans Pattern Anal Mach Intell
Asunto de la revista:
INFORMATICA MEDICA
Año:
2008
Tipo del documento:
Article
Pais de publicación:
Estados Unidos