An investigation of the use of high performance computing for multiscale color image smoothing using mathematical morphology

The use of mathematical morphology in lowand mid-level image processing and computer vision applications has allowed the development of a class of techniques for analyzing shape information in color images. These techniques have shown to be useful in image enhancement, segmentation, and analysis. In this paper, we develop and test scalable parallel algorithms necessary to implement a class of morphological filters on a parallel computer, specifically, the MasPar MP-1. We examine the issues relative to the parallel implementation of the algorithms and show that real-time enhancement of high resolution color images is possible.