High Performance Computing in Remote Sensing

Antonio J. Plaza, Chein-I Chang

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October 18, 2007 by Chapman and Hall/CRC
Reference - 496 Pages - 168 B/W Illustrations
ISBN 9781584886624 - CAT# C6625
Series: Chapman & Hall/CRC Computer and Information Science Series

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Features

  • Provides a state-of-the-art look at the HPC techniques—including cluster computers, workstation and grid networks, field programmable gate arrays (FPGAs), and graphics processing units (GPUs)—used to solve remote sensing problems
  • Presents well-established processing techniques for data acquisition, calibration, correction, target detection/classification, image segmentation, model inversion, and visualization
  • Includes several chapters that focus on hyperspectral imaging
  • Features contributors from world-renowned universities, NASA, the European Space Agency, and the Aerospace Corporation, providing insight into novel developments and realistic applications in the areas of security and defense, computer engineering, and Earth, space, and environmental sciences
  • Contains more than 200 high-quality figures and tables to promote a better understanding of the concepts described
  • Summary

    Solutions for Time-Critical Remote Sensing Applications

    The 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 Sensing is 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 Ideas

    The 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.