Distributed high-performance computation for remote sensing
SC '97 Proceedings of the 1997 ACM/IEEE conference on Supercomputing
MPI: The Complete Reference
ICCS 2009 Proceedings of the 9th International Conference on Computational Science
Preliminary through-out research on parallel-based remote sensing image processing
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
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Remote sensing image processing needs high performance computing to answer the fast growing data and requirement. Cluster-based parallel remote sensing image processing shows an effective way to overcome it. With an example of PIPS, paper gives basic theory of it, such as system structure, parallel model, and data distribution strategy and software integration and so on. Many experiments have proved that such technology can afford a receivable parallel efficiency with low cost hardware equipment. Moreover, it is friendly for experts who know remote sensing applications well and parallel computing less in developing their own parallel application implementations.