Toolkit for parallel image processing
Jeffrey M. Squyres, Andrew Lumsdaine, Robert Louis Stevenson · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
In this paper, we present the design and implementation of a parallel image processing software library (the Parallel Image Processing Toolkit). The Toolkit not only supplies a rich set of image processing routines, it is designed principally as an extensible framework containing generalized parallel computational kernels to support image processing. Users can easily add their own image processing routines without knowledge or explicit use of the underlying data distribution mechanisms or parallel computing model. Shared memory and multi-level memory hierarchies are exploited to achieve high performance on each node, thereby minimizing overall parallel execution time. Multiple load balancing schemes have been implemented within the parallel framework that transparently distribute the computational load evenly on a distributed memory computing environment. Inside the Toolkit, a message-passing model of parallelism is designed around the Message Passing Interface standard. Experimental results are presented to demonstrate the parallel speedup obtained with the Parallel Image Processing Toolkit in a typical workstation cluster with some common image processing tasks.