A Gauss-Markov Model for Hyperspectral Texture Analysis of Urban Areas

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http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1044850

16th International Conference on Patt ...

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	ASCII Text	x
	Guillaume Rellier, Xavier Descombes, Josiane Zerubia, Frédéric Falzon, "A Gauss-Markov Model for Hyperspectral Texture Analysis of Urban Areas," Pattern Recognition, International Conference on, vol. 1, pp. 10692, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 1, 2002.

	BibTex	x
	@article{ 10.1109/ICPR.2002.1044850, author = {Guillaume Rellier and Xavier Descombes and Josiane Zerubia and Frédéric Falzon}, title = {A Gauss-Markov Model for Hyperspectral Texture Analysis of Urban Areas}, journal ={Pattern Recognition, International Conference on}, volume = {1}, year = {2002}, issn = {1051-4651}, pages = {10692}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1044850}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pattern Recognition, International Conference on TI - A Gauss-Markov Model for Hyperspectral Texture Analysis of Urban Areas SN - 1051-4651 SP EP A1 - Guillaume Rellier, A1 - Xavier Descombes, A1 - Josiane Zerubia, A1 - Frédéric Falzon, PY - 2002 KW - null VL - 1 JA - Pattern Recognition, International Conference on ER -

Guillaume Rellier, INRIA

Xavier Descombes, INRIA

Josiane Zerubia, INRIA

Frédéric Falzon, Alcatel Space Industries

In this paper we tackle the problem of texture segmentation using a joint spectral and spatial analysis of pixel distribution. Hyperspectral images are considered and using a Markovian model we develop a vectorial approach for this image type. A classification algorithm using this model has been implemented for extracting and classifying urban areas. Results obtained from AVIRIS images are shown.

Citation:

Guillaume Rellier, Xavier Descombes, Josiane Zerubia, Frédéric Falzon, "A Gauss-Markov Model for Hyperspectral Texture Analysis of Urban Areas," icpr, vol. 1, pp.10692, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 1, 2002

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