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 theis class of algorithms. We have developed a special programming language call 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.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1987
Accession Number
ADA184330

Entities

People

  • I-chen Wu
  • Jon A. Webb
  • Leonard G. Hamey

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Application Software
  • Cells
  • Change Detection
  • Computations
  • Computer Programming
  • Computers
  • Computing System Architectures
  • Debugging
  • Detection
  • Image Processing
  • Language
  • Lisp Programming Language
  • Operating Systems
  • Programming Languages
  • Serial Processors
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Computer Science.
  • Computer Vision.
  • Operations Research