Multi-spectral Texture Characterisation for Remote Sensing Image Segmentation
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Scholar |
Otros documentos de la autoría: Pla, Filiberto; Gracia, Gema; García-Sevilla, Pedro; Mirmehdi, Majid; Xie, Xianghua
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/54899
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http://dx.doi.org/10.1007/978-3-642-02172-5_34 |
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Título
Multi-spectral Texture Characterisation for Remote Sensing Image SegmentationFecha de publicación
2009Editor
Springer Berlin HeidelbergISBN
978-3-642-02172-5Cita bibliográfica
PLA, F., et al. Multi-spectral Texture Characterisation for Remote Sensing Image Segmentation. En: Pattern Recognition and Image Analysis: 4th Iberian Conference, IbPRIA 2009 Póvoa de Varzim, Portugal, June 10-12, 2009 Proceedings, p. 257-264. Springer Berlin Heidelberg, 2009. (Lecture Notes in Computer Science; 5524) ISBN 978-3-642-02172-5Tipo de documento
info:eu-repo/semantics/bookPartVersión de la editorial
http://link.springer.com/chapter/10.1007/978-3-642-02172-5_34Palabras clave / Materias
Resumen
A multi-spectral texture characterisation model is proposed, the Multi-spectral Local Differences Texem – MLDT, as an affordable approach to be used in multi-spectral images that may contain large number of bands. The ... [+]
A multi-spectral texture characterisation model is proposed, the Multi-spectral Local Differences Texem – MLDT, as an affordable approach to be used in multi-spectral images that may contain large number of bands. The MLDT is based on the Texem model. Using an inter-scale post-fusion strategy for image segmentation, framed in a multi-resolution approach, we produce unsupervised multi-spectral image segmentations. Preliminary results on several remote sensing multi-spectral images exhibit a promising performance by the MLDT approach, with further improvements possible to model more complex textures and add some other features, like invariance to spectral intensity. [-]
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