Image classification using spectral and spatial information based on MRF models.
IEEE Trans Image Process
; 4(9): 1333-9, 1995.
Article
en En
| MEDLINE
| ID: mdl-18292031
ABSTRACT
A new criterion for classifying multispectral remote sensing images or textured images by using spectral and spatial information is proposed. The images are modeled with a hierarchical Markov Random Field (MRF) model that consists of the observed intensity process and the hidden class label process. The class labels are estimated according to the maximum a posteriori (MAP) criterion, but some reasonable approximations are used to reduce the computational load. A stepwise classification algorithm is derived and is confirmed by simulation and experimental results.
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Banco de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
IEEE Trans Image Process
Asunto de la revista:
INFORMATICA MEDICA
Año:
1995
Tipo del documento:
Article