Authored by a panel of experts in the field, this book focuses on hyperspectral image analysis, systems, and applications. With discussion of application-based projects and case studies, this professional reference will bring you up-to-date on this pervasive technology, wether you are working in the military and defense fields, or in remote sensing technology, geoscience, or agriculture.
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From the Back Cover
A Unique Synthesis of Hyperspectral Imaging with Theory and Applications, Written by Pioneers in the Field
The rapid growth of interest in the use of hyperspectral imaging as a powerful remote sensing technique has been accompanied by hundreds of articles published in journals and conference proceedings. With new findings and applications dispersed across numerous sources, this contributed work provides a much-needed synthesis of what is known, what can be expected from current research and development, and what new research is needed.
The book's twenty-five contributors represent some of the field's most important innovators and pioneers from around the world. It begins with an overview written by the editor that discusses the design theory underlying the development of hyperspectral imaging techniques. This overview also provides a brief introduction to each of the book's thirteen chapters, with an emphasis on the interconnections among them. Chapters are organized into three parts: Tutorials, Theory, and Applications.
Among the spectrum of topics covered are imaging systems, data modeling, data representation, band selection and partition, classification, and data compression.
Readers discover a wide range of current and emerging techniques for surface material identification, evaluation, and analysis of materials. Many of the chapters feature case studies that demonstrate applications in defense and homeland security, intelligence, environmental sciences, geology, and agriculture.
Researchers and practitioners throughout the field of remote sensing will find this volume an exceptionally valuable reference that brings together, analyzes, and synthesizes the many research findings and emerging applications in hyperspectral imaging.
About the Author
Chein-I Chang, PHD, is Professor in the Department of Computer Sciences and Electrical Engineering at the University of Maryland, Baltimore County, where he directs the Remote Sensing Signal and Image Processing Laboratory. Dr. Chang is a Fellow of SPIE, the International Society for Optical Engineering, for his achievements in hyperspectral image processing. He is Associate Editor of the IEEE Transactions on Geoscience and Remote Sensing and the author of Hyperspectral Imaging: Techniques for Spectral Detection and Classification.
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Key Phrases - Statistically Improbable Phrases (SIPs):
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hyperspectral data exploitation, remote sensing, mixed spectra, spectral identification system, optimal band sets, unmix hyperspectral data, semilabeled samples, unmixing hyperspectral data, band selection technique, semilabeled patterns, endmember variance, material identification results, stochastic mixing model, terrain categorization, study spectral region, subpixel object detection, nonparametric weighted feature extraction, hyperspectral classification, extended morphological profiles, hyperspectral image classification, topography modulation, unitary bit, endmember spectra, hyperspectral imaging systems, hyperspectral data analysis Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, John Wiley, Chang Copyright, Monte Carlo, Image Processing, Jasper Ridge, Journal of Geophysical Research, Academic Press, Ultraspectral Imagery, Signal Processing Magazine, Pattern Recognition Letters, Bitumen Ref, Brick Ref, Shadow Ref, Indian Pine, Average Overall Accuracy Accuracy, Meadow Ref, Bare Soil Ref, Tree Ref, Gravel Ref, Metal Sheet Ref, Applied Optics, Second-Stage Process, Kluwer Academic Publishers, Purdue University Browse Sample Pages:
Table of Contents | First Pages | Index | Back Cover | Surprise Me!
hyperspectral data exploitation, remote sensing, mixed spectra, spectral identification system, optimal band sets, unmix hyperspectral data, semilabeled samples, unmixing hyperspectral data, band selection technique, semilabeled patterns, endmember variance, material identification results, stochastic mixing model, terrain categorization, study spectral region, subpixel object detection, nonparametric weighted feature extraction, hyperspectral classification, extended morphological profiles, hyperspectral image classification, topography modulation, unitary bit, endmember spectra, hyperspectral imaging systems, hyperspectral data analysis Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, John Wiley, Chang Copyright, Monte Carlo, Image Processing, Jasper Ridge, Journal of Geophysical Research, Academic Press, Ultraspectral Imagery, Signal Processing Magazine, Pattern Recognition Letters, Bitumen Ref, Brick Ref, Shadow Ref, Indian Pine, Average Overall Accuracy Accuracy, Meadow Ref, Bare Soil Ref, Tree Ref, Gravel Ref, Metal Sheet Ref, Applied Optics, Second-Stage Process, Kluwer Academic Publishers, Purdue University Browse Sample Pages:
Table of Contents | First Pages | Index | Back Cover | Surprise Me!
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