Abstract
The aim of this work is to study the IR spectra (reflectance and absorbance) of samples from the Central Volcanic Range (CVR) of Costa Rica and their relationship as outliers in anomaly detection. We investigate the spectral characteristics of variable reflectance in the pattern recognition of geological materials in several single hyperspectral scenes. It is assumed no prior knowledge of the targets in anomaly detection. Thus, the pixels are automatically separated according to their spectral information, significantly differentiated with respect to a background, either globally for the full scene, or locally by the image segmentation. Spectral ranges of the visible-near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) from hyperspectral data cubes of HyMAP and MASTER have been used. Several experiments on natural scenarios of the CVR and semi-urban of different complexity, have been designed, analyzing the behavior of the standard RX anomaly detector and different approaches based on image projection and dimensionality reduction. First results and their consequences as terrestrial analogs in planetary exploration are discussed.
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References
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Rejas, J.G., Martínez, R., Marchamalo, M., Bonatti, J., Martínez-Frías, J. (2014). Spectral Analysis for Anomaly Detection in the Central Volcanic Range, Costa Rica. Implications for Planetary Geology. In: Pardo-Igúzquiza, E., Guardiola-Albert, C., Heredia, J., Moreno-Merino, L., Durán, J., Vargas-Guzmán, J. (eds) Mathematics of Planet Earth. Lecture Notes in Earth System Sciences. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32408-6_170
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DOI: https://doi.org/10.1007/978-3-642-32408-6_170
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