"Hyperspectral Data Algorithm Design and Analysis "is a culmination of the research conducted in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. Specifically, it treats hyperspectral image processing and hyperspectral signal processing as separate subjects in two different categories. Most materials covered in this book can be used in conjunction with the author's first book, "Hyperspectral Techniques for Spectral Detection and Classification, "without much overlap.Many results in this book are either new or have not been explored, presented, or published in the public domain. These include various aspects of endmember extraction, unsupervised linear spectral mixture analysis, hyperspectral information compression, hyperspectral signal coding and characterization, as well as applications to conceal target detection, multispectral imaging, and magnetic resonance imaging. "Hyperspectral Data Processing "contains eight major Part provides fundamentals of hyperspectral data processingPart offers various algorithm designs for endmember extractionPart derives theory for supervised linear spectral mixture analysisPart designs unsupervised methods for hyperspectral image analysisPart explores new concepts on hyperspectral information compressionParts VI & develops techniques for hyperspectral signal coding and characterizationPart presents applications in multispectral imaging and magnetic resonance imaging"Hyperspectral Data Processing "compiles an algorithm compendium with MATLAB codes in an appendix to help readers implement many important algorithms developed in this book and write their own program codes without relying on software packages."Hyperspectral Data Processing "is a valuable reference for those who have been involved with hyperspectral imaging and its techniques, as well those who are new to the subject.