Heterogeneous Parallel Computing in Remote Sensing Applications: Current Trends and Future Perspectives

Heterogeneous networks of computers have rapidly become a very promising commodity computing solution, expected to play a major role in the design of high performance computing systems for remote sensing missions. Currently, only a few parallel processing strategies are available in this research area, and most of them assume homogeneity in the underlying computing platform. This paper develops several highly innovative heterogeneous parallel algorithms for information extraction from highdimensional remotely sensed images, with particular emphasis on target detection and land-cover mapping applications. Experimental results are presented in the context of a realistic application, using real data collected by NASA’s Jet Propulsion Laboratory over the World Trade Center complex in New York City after September 11th,

• Type: Conference
• Year: 2006
• Where: CLUSTER
• Authors: Antonio J. Plaza
• Keywords: CLUSTER 2006, Cluster Computing, Commodity Computing Solution, Heterogeneous Parallel Algorithms, Parallel Processing Strategies