Book description
Hyperspectral Data Processing: 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 Imaging: 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 sections:
- Part I: provides fundamentals of hyperspectral data processing
- Part II: offers various algorithm designs for endmember extraction
- Part III: derives theory for supervised linear spectral mixture analysis
- Part IV: designs unsupervised methods for hyperspectral image analysis
- Part V: explores new concepts on hyperspectral information compression
- Parts VI & VII: develops techniques for hyperspectral signal
coding and characterization
- Part VIII: 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.
CHEIN-I CHANG, PhD, is a Professor in the Department of
Computer Science and Electrical Engineering at the University of
Maryland, Baltimore County. He established the Remote Sensing Signal
and Image Processing Laboratory and conducts research in designing and
developing signal processing algorithms for hyperspectral imaging,
medical imaging, and documentation analysis. A Fellow of IEEE and
SPIE, Dr. Chang has published over 125 refereed journal articles,
including more than forty papers in the IEEE Transaction on
Geoscience and Remote Sensing. In addition to authoring
Hyperspectral Imaging: Techniques for Spectral Detection and
Classification, as well as editing two books, Hyperspectral
Data Exploitation: Theory and Applications and Recent
Advances in Hyperspectral Signal and Imaging Processing and
co-editing one book, High Performance Computing in Remote
Sensing, he holds five patents and has several pending.
