A block size optimization algorithm for Parallel Image Processing

The aim of this work is to define a strategy for rectangular block partitioning that can be adapted to the number of available processing units in a parallel processing machine, regardless of the input data size. With this motivation, an algorithm for optimal vector block partitioning is introduced and tested in a typical parallel image application. The proposed algorithm provides a novel partition method that reduces data sharing between blocks and maintains block sizes as equal as possible for any input size.