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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.

Key Technologies Research on Building a Cluster-Based Parallel Computing System for Remote Sensing