International Journal of High Performance Computing Applications
Grid Based Training Environment for Earth Observation
GPC '09 Proceedings of the 4th International Conference on Advances in Grid and Pervasive Computing
Examining the potential parallel scalability of a fuzzy semi-supervised classification algorithm
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
Future Generation Computer Systems
Journal of Signal Processing Systems
Parallel morphological processing of hyperspectral image data on heterogeneous networks of computers
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Satellite image structure analysis with the GRID technologies
MTPP'10 Proceedings of the Second Russia-Taiwan conference on Methods and tools of parallel programming multicomputers
EURASIP Journal on Advances in Signal Processing
Clusters versus GPUs for parallel target and anomaly detection in hyperspectral images
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
Grid-enabled high-performance quantitative aerosol retrieval from remotely sensed data
Computers & Geosciences
Remote sensing image information mining with HPC cluster and DryadLINQ
Proceedings of the 49th Annual Southeast Regional Conference
SSCCIP: a framework for building distributed high-performance image processing technologies
PaCT'11 Proceedings of the 11th international conference on Parallel computing technologies
A new parallel tool for classification of remotely sensed imagery
Computers & Geosciences
Use of FPGA or GPU-based architectures for remotely sensed hyperspectral image processing
Integration, the VLSI Journal
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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 andvideo processing. Each subsequent chapter illustrate s 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.