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Other titles in the Chapman & Hall/CRC Computer and Information Science series:
High Performance Computing in Remote Sensing (Chapman & Hall/CRC Computer and Information Science)by Plaza J. Plaza
Synopses & Reviews
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.
Book News Annotation:
Focusing on the computational complexity of algorithms designed for parallel computing and processing, some of these 18 articles also apply to multimedia and video processing as well as to remote sensing. Topics include high-performance computer (HPC) architectures for remote sensing data analysis, computer architectures for multimedia and video analysis, parallel implementation of the ORASIS algorithm and recursive approximation of an unsupervised hierarchical segmentation algorithm, computing for analysis and modeling of hyper-spectral imagery, parallel implementation of morphological neural networks for hyper-spectral image analysis, parallel wild land fire monitoring and tracking, grids for remote sensing, software for data analysis, imaging spectrometers as analysis tools, high-performance reconfigurable computing systems, energy reduction in processing, and real-time online processing of imagery. The articles are universally well-illustrated and although are written for those in the field are accessible to non-experts as well as for upper-level undergraduate or graduate students. Annotation ©2008 Book News, Inc., Portland, OR (booknews.com)
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