Architecture-independent global image processing

Abstract

A specialized language, called Adapt, for local and global image processing on parallel processors is presented. Adapt is based on a split and merge model. The input image is split into sections, which are processed separately on different processors, and the results are merged using a function written by the user. This model is quite general; any image processing operation that can be computed from top to bottom or from bottom to top on an image can be computed with it. The use of Adapt is illustrated with several programs for important global operations, including histogram, Hough transform, minimum bounding rectangle, and connected components. A preliminary implementation of Adapt exists on the Carnegie Mellon Warp machine. Performance figures from this implementation are provided. A description of how Adapt can be implemented on other architectures is given.<>