Approaches to classification of multichannel images

Vladimir Lukin, Nikolay Ponomarenko, Andrey Kurekin, Kenneth Lever, Oleksiy Pogrebnyak, Luis Pastor Sanchez Fernandez

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

10 Citas (Scopus)

Resumen

The comparison of different approaches to classification of multichannel remote sensing images obtained by spaceborne imaging systems is presented. It is demonstrated that it is reasonable to compress original noisy images with appropriate compression ratio and then to classify the decompressed images rather than original data. Two classifiers are considered: based on radial basis function neural network and support vector machine. The latter one produces slightly better classification results.

Idioma originalInglés
Título de la publicación alojadaProgress in Pattern Recognition, Image Analysis and Applications - 11th Iberoamerican Congress in Pattern Recognition, CIARP 2006, Proceedings
EditorialSpringer Verlag
Páginas794-803
Número de páginas10
ISBN (versión impresa)3540465561, 9783540465560
DOI
EstadoPublicada - 2006
Evento11th Iberoamerican Congress in Pattern Recognition, CIARP 2006 - Cancun, México
Duración: 14 nov. 200617 nov. 2006

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen4225 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia11th Iberoamerican Congress in Pattern Recognition, CIARP 2006
País/TerritorioMéxico
CiudadCancun
Período14/11/0617/11/06

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