Hyperspectral Data Exploitation: Theory and Applications

Description

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.

 

1. Chapter 1: Overview (Chein-I Chang)

PART I: TUTORALS

2. Chapter 2. Hyperspectral Imaging Systems (John P. Kerekes and John R. Schott)

Chapter 3. Information-Processed Matched Filters for Hyperspectral Target Detection and Classification (Chein-I Chang)

PART II: THEORY

Chapter 4. An Optical Real-Time Adaptive Spectral Identification System (ORASIS) (Jeffery H. Bowles and David B. Gillis)

Chapter 5: Stochastic Mixture Modeling (Michael T. Eismann1 and David W. J. Stein)

Chapter 6. Unmixing Hyperspectral Data: Independent and Dependent Component Analysis (Jose M.P. Nascimento1 and Jose M.B. Dias)

Chapter 7. Maximum Volume Transform For Endmember Spectra Determination (Michael E. Winter)

Chapter 8. Hyperspectral Data Representation (X. Jia1 and John A. Richards)

Chapter 9. Optimal Band Selection and Utility Evaluation for Spectral Systems (Sylvia S. Shen)

Chapter 10. Feature Reduction for Classification Purpose (Sebastiano B. Serpico, Gabriele Moser and Andrea F. Cattoni)

Chapter 11. Semi-supervised Support Vector Machines for Classification of Hyperspectral Remote Sensing Images (Lorenzo Bruzzone, Mingmin Chi and Mattia Marconcini)

PART III: APPLICATIONS

Chapter 12. Decision Fusion for Hyperspectral Classification (Mathieu Fauvel, Jocelyn Chanussot and Jon Atli Benediktsson)

Chapter 13. Morphological Hyperspectral Image Classification: A Parallel Processing Perspective (Antonio J. Plaza)

Chapter 14. 3D Wavelet-Based Compression of Hyperspectral Imagery (James E. Fowler and Justin T. Rucker)