Overview
- Explores recursive structures in algorithm architecture
- Implements algorithmic recursive architecture in conjunction with progressive sample and band processing
- Derives Recursive Hyperspectral Sample Processing (RHSP) techniques according to Band-Interleaved Sample/Pixel (BIS/BIP) acquisition format
- Develops Recursive Hyperspectral Band Processing (RHBP) techniques according to Band SeQuential (BSQ) acquisition format for hyperspectral data
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (21 chapters)
-
Front Matter
-
Sample Spectral Statistics-Based Recursive Hyperspectral Sample Processing
-
Front Matter
-
-
Signature Spectral Statistics-Based Recursive Hyperspectral Sample Processing
-
Front Matter
-
-
Sample Spectral Statistics-Based Recursive Hyperspectral Band Processing
-
Front Matter
-
-
Signature Spectral Statistics-Based Recursive Hyperspectral Band Processing (RHBP)
-
Front Matter
-
Keywords
About this book
This book explores recursive architectures in designing progressive hyperspectral imaging algorithms. In particular, it makes progressive imaging algorithms recursive by introducing the concept of Kalman filtering in algorithm design so that hyperspectral imagery can be processed not only progressively sample by sample or band by band but also recursively via recursive equations. This book can be considered a companion book of author’s books, Real-Time Progressive Hyperspectral Image Processing, published by Springer in 2016.
Authors and Affiliations
About the author
Chein-I Chang is Professor with Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County. He established a 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. Dr. Chang has published over 146 referred journal articles including more than 50 papers in the IEEE Transaction on Geoscience and Remote Sensing alone and four patents with several pending on hyperspectral image processing. He authored two books, Hyperspectral Imaging: Techniques for Spectral Detection and Classification (Kluwer Academic Publishers, 2003) and Hyperspectral Data Processing: Algorithm Design and Analysis (Wiley, 2013). He also edited two books, Recent Advances in Hyperspectral Signal and Image Processing (Transworld Research Network, India, 2006) and Hyperspectral Data Exploitation: Theory and Applications (JohnWiley & Sons, 2007) and co-edited with A. Plaza a book on High Performance Computing in Remote Sensing (CRC Press, 2007). Dr. Chang has received his Ph.D. in Electrical Engineering from University of Maryland, College Park. He is a Fellow of IEEE and SPIE with contributions to hyperspectral image processing.
Bibliographic Information
Book Title: Real-Time Recursive Hyperspectral Sample and Band Processing
Book Subtitle: Algorithm Architecture and Implementation
Authors: Chein-I Chang
DOI: https://doi.org/10.1007/978-3-319-45171-8
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2017
Hardcover ISBN: 978-3-319-45170-1Published: 04 May 2017
Softcover ISBN: 978-3-319-83230-2Published: 08 May 2018
eBook ISBN: 978-3-319-45171-8Published: 23 April 2017
Edition Number: 1
Number of Pages: XXIII, 690
Number of Illustrations: 60 b/w illustrations, 233 illustrations in colour
Topics: Signal, Image and Speech Processing, Image Processing and Computer Vision, Pattern Recognition, Biometrics