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Synopsis

Hyperspectral Data Processing: Algorithm Design andAnalysis is a culmination of the research conducted in theRemote Sensing Signal and Image Processing Laboratory (RSSIPL) atthe University of Maryland, Baltimore County. Specifically, ittreats hyperspectral image processing and hyperspectral signalprocessing as separate subjects in two different categories. Mostmaterials covered in this book can be used in conjunction with theauthor’s first book, Hyperspectral Imaging: Techniques forSpectral Detection and Classification, without muchoverlap.

Many results in this book are either new or have not beenexplored, presented, or published in the public domain. Theseinclude various aspects of endmember extraction, unsupervisedlinear spectral mixture analysis, hyperspectral informationcompression, hyperspectral signal coding and characterization, aswell as applications to conceal target detection, multispectralimaging, and magnetic resonance imaging. Hyperspectral DataProcessing contains eight major sections:

  • Part I: provides fundamentals of hyperspectral dataprocessing
  • Part II: offers various algorithm designs for endmemberextraction
  • Part III: derives theory for supervised linear spectral mixtureanalysis
  • Part IV: designs unsupervised methods for hyperspectral imageanalysis
  • Part V: explores new concepts on hyperspectral informationcompression
  • Parts VI & VII: develops techniques for hyperspectralsignal coding and characterization
  • Part VIII: presents applications in multispectral imaging andmagnetic resonance imaging

Hyperspectral Data Processing compiles an algorithmcompendium with MATLAB codes in an appendix to help readersimplement many important algorithms developed in this book andwrite their own program codes without relying on softwarepackages.

Hyperspectral Data Processing is a valuable reference forthose who have been involved with hyperspectral imaging and itstechniques, as well those who are new to the subject.

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