Hyperspectral Imaging: Techniques for Spectral Detection and
Classification is an outgrowth of the research conducted over the
years in the Remote Sensing Signal and Image Processing Laboratory
(RSSIPL) at the University of Maryland, Baltimore County. It
explores applications of statistical signal processing to
hyperspectral imaging and further develops non-literal (spectral)
techniques for subpixel detection and mixed pixel classification.
This text is the first of its kind on the topic and can be
considered a recipe book offering various techniques for
hyperspectral data exploitation. In particular, some known
techniques, such as OSP (Orthogonal Subspace Projection) and CEM
(Constrained Energy Minimization) that were previously developed in
the RSSIPL, are discussed in great detail. This book is
self-contained and can serve as a valuable and useful reference for
researchers in academia and practitioners in government and
industry.
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