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Hyperspectral Imaging is a comprehensive exploration of the different analytical methodologies applied on hyperspectral imaging and a state-of-the-art analysis of the applications in different scientific and industrial areas. The different application fields in which hyperspectral imaging has clearly demonstrated its advantages have bloomed in recent years. This is due to the adaptation of remote sensing cameras to laboratory and industrial environments and, importantly, the advances in data managing systems and development of new and faster algorithms. It is evident that such technology calls for powerful and reliable data mining technologies able to extract the desirable information from the scanned sample.
This book collects for the first time a comprehensive study of the main multivariate algorithms that have been used for hyperspectral image analysis in the different fields of application. The benefits, drawbacks, and suitability of each are fully discussed along with examples of applications. Moreover, the book collects the state-of-the art of the machinery for hyperspectral image acquisition as well as a critical assessment of the usage of hyperspectral imaging in diverse scientific fields.