Karhunen-Loeve Transform: An Exercise in Simple Image-Processing Parallel Pipelines

Abstract

Practical parallelizations of multi-phased low-level image-processing algorithms may require working in batch mode. The features of a new processing model, employing a pipeline of processor farms, are described. A simple exemplar, the Karhunen-Loeve transform, is prototyped on a network of processors running a real-time operating system. The design trade-offs for this and similar algorithms are indicated. In the manner of co-design, eventual implementation on large- and fine-grained hardware is considered.  The chosen exemplar is shown to have some features, such as strict sequencing and unbalanced processing phases, which militate against a comfortable implementation.