Visualization and Logical Binding of Hyperspectral Data Using QuickViz and SAADA

Computer Science – Databases

Scientific paper

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Scientific paper

Next generation integral-field spectrographs (IFS) such as MUSE will record large hyperspectral cubes and thus generate a huge amount of observational and interpretable data. Their visualization remains a problematic and crucial task before any processing. In addition, observation parameters such as variance values may also be associated to each cube and be involved in the scientific interpretation of the data. In this paper, we propose a new software named QuickViz that provides a set of basic and advanced features enabling the exploration of such hyperspectral images with their related observation parameters. This new software is designed in Java as an Aladin plug-in and thus extends its hyperspectral functionalities while managing all the interactions between cubes and extracted spectra. Moreover, the specifications of the SAADA application allowing to automatically generate astronomical relational databases give the ability to easily explore such large data sets with respect to their complex relationships.

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