Abstract: Key idea of this work is to provide a open source frame work for image processing that can be run on different parallel processing platforms. Parallel processing is necessary because sensors are producing more data at faster rates. This presentation looks at wide area motion imagery (WAMI) data from LAIR public released data set. Traditional S&E tools don’t scale in the cloud in terms of performance or cost. Open source software along with cloud computing becomes an enabler of affordable parallel processing because license costs per node are minimized plus computation has become a commodity. This presentation uses Enthought Python Distribution with parallel processing support via built-in ZeroMQ. This process can be automated to produce large amounts of data with minimal human effort.
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