Parallel Processing Strategies for Large SAR Image Data Sets in a Distributed Environment

Abstract.

Image processing of synthetic aperture radar (SAR) images is challenging due to distributed storage of input data sets and since appropriate algorithms are complex and time-consuming. Computers able to process these data in acceptable time usually are not at user's site. Our Concurrent and Distributed Image Processing (CDIP) system overcomes these problems and provides a platform-independent, transparent environment based on Java, CORBA and NetSolve. Users query a broker to find remote, high-performance servers on which the algorithms actually are executed.

Key algorithms like image matching and Shape-from-Shading were parallelized mainly using MPI, and ported onto suitable computer architectures. Our experiments showed that all algorithms perform well, and they further proved the concept of CDIP to be beneficial: Usability of all integrated algorithms was significantly improved, mainly due to less user-centered network traffic, simple access to supercomputers, the creation of method sequences, and easy-to-use and well maintained algorithms.