Low-Level Vision on Warp and the Apply Programming Model

Abstract

In the course of implementing low-level (image to image) vision algorithms on Warp, we have understood the mapping of this class of algorithms well enough so that the programming of these algorithms is now a straightforward and stereotypical task. The partitioning method used is input partitioning, which provides an efficient, natural implementation of this class of algorithms. We have developed a special programming language called Apply, which reduces the problem of writing the algorithm for this class of programs to the task of writing the function to be applied to a window around a single pixel. Apply provides a method for programming Warp in these applications which is easy, consistent. and efficient. Apply is application specific, but machine independent - it is possible to implement versions of Apply which run efficiently on a wide variety of computers. We describe implementations of Apply on Warp, UNIX and the Hughes HBA, and sketch implementation on bit-serial processor arrays and distributed memory machines.