High Performance Computing in Remote Sensing
One of the first volumes to explore state-of-the-art HPC techniques in the context of remote sensing problems, this book focuses on the computational complexity of algorithms that are designed for parallel computing and processing. It addresses key computing concepts and developments in remote sensi...
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| Main Authors | , |
|---|---|
| Format | eBook Book |
| Language | English |
| Published |
Boca Raton
Chapman and Hall/CRC
2008
Chapman & Hall CRC Press LLC CRC Press |
| Edition | 1 |
| Series | Chapman & Hall/CRC computer and information science series |
| Subjects | |
| Online Access | Get full text |
| ISBN | 1584886625 9781584886624 |
| DOI | 10.1201/9781420011616 |
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| Abstract | One of the first volumes to explore state-of-the-art HPC techniques in the context of remote sensing problems, this book focuses on the computational complexity of algorithms that are designed for parallel computing and processing. It addresses key computing concepts and developments in remote sensing and covers application areas not necessarily related to remote sensing, such as multimedia and video processing. Each chapter illustrates a specific parallel computing paradigm, including multiprocessor (cluster-based) systems, large-scale and heterogeneous networks of computers, grid computing platforms, and specialized hardware architectures for remotely sensed data analysis and interpretation. |
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| AbstractList | Solutions for Time-Critical Remote Sensing ApplicationsThe recent use of latest-generation sensors in airborne and satellite platforms is producing a nearly continual stream of high-dimensional data, which, in turn, is creating new processing challenges. To address the computational requirements of time-critical applications, researchers. One of the first volumes to explore state-of-the-art HPC techniques in the context of remote sensing problems, this book focuses on the computational complexity of algorithms that are designed for parallel computing and processing. It addresses key computing concepts and developments in remote sensing and covers application areas not necessarily related to remote sensing, such as multimedia and video processing. Each chapter illustrates a specific parallel computing paradigm, including multiprocessor (cluster-based) systems, large-scale and heterogeneous networks of computers, grid computing platforms, and specialized hardware architectures for remotely sensed data analysis and interpretation. Solutions for Time-Critical Remote Sensing ApplicationsThe recent use of latest-generation sensors in airborne and satellite platforms is producing a nearly continual stream of high-dimensional data, which, in turn, is creating new processing challenges. To address the computational requirements of time-critical applications, researchers have begun incorporating high performance computing (HPC) models in remote sensing missions. High Performance Computing in Remote Sensingis one of the first volumes to explore state-of-the-art HPC techniques in the context of remote sensing problems. It focuses on the computational complexity of algorithms that are designed for parallel computing and processing. A Diverse Collection of Parallel Computing Techniques and Architectures The book first addresses key computing concepts and developments in remote sensing. It also covers application areas not necessarily related to remote sensing, such as multimedia and video processing. Each subsequent chapter illustrates a specific parallel computing paradigm, including multiprocessor (cluster-based) systems, large-scale and heterogeneous networks of computers, grid computing platforms, and specialized hardware architectures for remotely sensed data analysis and interpretation. An Interdisciplinary Forum to Encourage Novel IdeasThe extensive reviews of current and future developments combined with thoughtful perspectives on the potential challenges of adapting HPC paradigms to remote sensing problems will undoubtedly foster collaboration and development among many fields. |
| Author | Plaza, Antonio J. Chang, Chein-I |
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| Copyright | 2008 by Taylor & Francis Group, LLC Chapman & Hall/CRC is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works |
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| Edition | 1 1st edition |
| Editor | Plaza, Antonio J. Chang, Chein-I |
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| Keywords | High Performance Computing Endmember Extraction Algorithm Data Sets Imaging Spectroscopy Hyperspectral Imaging PPI Execution Time Remote Sensing Problems Hyperspectral Data NASA’s Goddard Space Flight Pixel Vector Hyperspectral Image Analysis Remote Sensing Remote Sensing Data CEM CORDIC AVIRIS Data Set Imaging Spectrometer Grid Computing Environments Systolic Array Grid Services Hyperspectral Data Sets Endmember Extraction Reconfigurable Computing Hyperspectral Image Processing |
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| Notes | Includes bibliographical references and index |
| OCLC | 935266155 |
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| Snippet | One of the first volumes to explore state-of-the-art HPC techniques in the context of remote sensing problems, this book focuses on the computational... Solutions for Time-Critical Remote Sensing ApplicationsThe recent use of latest-generation sensors in airborne and satellite platforms is producing a nearly... |
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| SubjectTerms | High performance computing Remote sensing |
| TableOfContents | Front cover -- Contents -- List of Tables -- List of Figures -- Acknowledgments -- About the Editors -- Contributors -- Chapter 1. Introduction -- Chapter 2. High-Performance Computer Architectures for Remote Sensing Data Analysis: Overview and Case Study -- Chapter 3. Computer Architectures for Multimedia and Video Analysis -- Chapter 4. Parallel Implementation of the ORASIS Algorithm for Remote Sensing Data Analysis -- Chapter 5. Parallel Implementation of the Recursive Approximation of an Unsupervised Hierarchical Segmentation Algorithm -- Chapter 6. Computing for Analysis and Modeling of Hyperspectral Imagery -- Chapter 7. Parallel Implementation of Morphological Neural Networks for Hyperspectral Image Analysis -- Chapter 8. Parallel Wildland FIre Monitoring and Tracking Using Remotely Sensed Data -- Chapter 9. An Introduction to Grids for Remote Sensing Applications -- Chapter 10. Remote Sensing Grids: Architecture and Implementation -- Chapter 11. Open Grid Services for Envisat and Earth Observation Applications -- Chapter 12. Design and Implementation of a Grid Computing Environment for Remote Sensing -- Chapter 13. A Solutionware for Hyperspectral Image Processing and Analysis -- Chapter 14. AVIRS and Related 21st Century Imaging Spectrometers for Earth and Spac Science -- Chapter 15. Remote Sensing and High-Performance Reconfigurable Computing Systems -- Chapter 16. FPGA Design for Real-Time Implementation of Constrained Energy Minimization for Hyperspectral Target Detection -- Chapter 17. Real-Time Online Processing of Hyperspectral Imagery for Target Detection and Discrimination -- Chapter 18. Real-Time Onboard Hyperspectral Image Processing Using Programmable Graphics Hardware -- Index -- Back cover |
| Title | High Performance Computing in Remote Sensing |
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