High Performance Computing in Remote Sensing
Antonio J. Plaza
Sold by AHA-BUCH GmbH, Einbeck, Germany
AbeBooks Seller since 14 August 2006
New - Hardcover
Condition: Neu
Quantity: 1 available
Add to basketSold by AHA-BUCH GmbH, Einbeck, Germany
AbeBooks Seller since 14 August 2006
Condition: Neu
Quantity: 1 available
Add to basketNeuware - Explores various HPC techniques in the context of remote sensing problems. This book addresses key computing concepts and developments in remote sensing. It covers application areas not necessarily related to remote sensing, such as multimedia and video processing.
Seller Inventory # 9781584886624
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.
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