Hybrid computational methods for hyperspectral image analysis

Authors:
Miguel A. Veganzones;Manuel Graña
Affiliations:
Grupo de Inteligencia Computacional, Universidad del País Vasco, Spain;Grupo de Inteligencia Computacional, Universidad del País Vasco, Spain
Venue:
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
Year:
2012

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Abstract

In this paper we provide a brief review of recent advances in computational methods for hyperspectral image analysis with emphasis in hybrid approaches. Hyperspectral imagery acquisition and hyperspectral analysis are growing fields. The analysis of hyperspectral images will have an increasing impact in several application areas, i.e., Earth observation, planetology, food industry, quality processes, medicine, etc. Hyperspectral image analysis is itself a hybrid process that chains different computational techniques. We focus on dimensionality reduction and spectral unmixing which are fundamental parts of hyperspectral image analysis.