A high level language for parallel image processing

Abstract

Most published research in the field of parallel image processing has tended to be in the areas of parallel architectures and parallel algorithms. Work on the development of software tools such as languages has generally been less extensive. This paper describes some research which is intended to redress the balance a little, by describing I-BOL-an application-specific high level programming language intended for implementing low-level image processing applications on parallel architectures. In particular, I-BOL has been designed to be capable of implementation on distributed memory parallel machines such as transputer networks. This paper introduces the core concepts of I-BOL: its view of an image as a set of tuples; user-defined neighbourhood functions; and I-BOL's facilities for recursive image processing. Solutions to a number of example problems illustrate particular aspects of the notation, including the Distance Transform, Histogram Equalization and the Hough Transform. Some consideration is given to the parallel aspects of the current implementation of I-BOL on a pipeline of transputers. A few performance measurements are quoted, giving execution times for the chosen examples on various sizes of transputer work.