Parallel implementations of selected image processing techniques
In this thesis we present parallel implementations of one local (convolution) and one global (regular moment extraction) image processing technique on a multi-transputer system. Issues relevant to implementation design, including Computational algorithm selection, initial data pass, and topology selection are discussed. Linear speedups in the convolution implementations are observed whereas the efficiency of the regular moment programs decreases as the number of transputers increases. Analysis of the implementations including parallel time complexity functions and observations about data passing and topology selection is given. Two theoretical performance models based on the implementations closely match empirical timing results.