Skip to main content

Abstract

As an alternative to the true pyramidal arrays of processors other specialized hardware solutions have been proposed to exploit multiresolution approaches. Among these the most popular is the family of pipeline architectures special- ized for decimation and expansion of the image size. The major systems in this class are PVM, and HCL/PIPE. These systems which are designed to perform foveation and tracking processes efficiently, are introduced in some detail.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. P. J. Burt and G. van der Wal, An architecture for multi-resolution, focal, image analysis, Proc. 10th Int. Conf. Pattern Recognition, Atlantic City, NJ, 1990, pp. 305–311.

    Google Scholar 

  2. E. W. Kent, M. O. Shneider, and R. Lumia, PIPE: pipelined image processing engine, J. Parallel Distrib. Comput. 2, 50–78 (1985).

    Article  Google Scholar 

  3. G. Grandlund and J. Arvidsson, The GOP image computer, in Fundamentals in Computer Vision (O. Faugeras, ed.), pp. 443–458, Cambridge University Press, Cambridge (1983).

    Google Scholar 

  4. K. Lundgren, D. Antonsson, J. Arvidsson, and G. H. Grandlund, GOP, a two stages microprogrammable pipelined image processor, Proc. 2nd Scandinavian Conf. Image Analysis, Helsinki, Finland, 1981, pp. 408–414.

    Google Scholar 

  5. G. Grandlund and J. Arvidsson, Computer architectures for image processing, Proc. 4nd Scandinavian Conf. Image Analysis, Trondheim, Norway, 1985.

    Google Scholar 

  6. P. J. Burt, C. H. Anderson, J. O. Sinniger, and G. van der Wal, A pipeline pyramid machine, in Pyramidal Systems for Computer Vision (V. Cantoni and S. Levialdi, eds.), pp. 133–152, Springer-Verlag, Berlin (1986).

    Chapter  Google Scholar 

  7. G. S. van der Wal, The Sarnoff pyramid chip, Proc. Workshop on Computer Architectures for Machine Perception (B. Zavidovique and P. L. Wendel, eds.), Paris, 1992, pp. 69–79.

    Google Scholar 

  8. P. J. Burt, Smart sensing in a pyramid vision machine, Proc. IEEE ,76(8), 1006–1014 (1988).

    Article  Google Scholar 

  9. C. H. Anderson, P. J. Burt, and G. van der Wal, Change detection and tracking using pyramid transform techniques, Proc. SPIE Conf. Intelligent Robots and Computer Vision, 1985, pp. 72–78.

    Google Scholar 

  10. P. J. Burt and G. van der Wal, An architecture for multiresolution, focal, image analysis, Proc. 10th Int. Conf. Pattern Recognition, Atlantic City, NJ, 1990, pp. 305–311.

    Google Scholar 

  11. P. J. Burt and G. van der Wal, Iconic image analysis with the pyramid vision machine, Proc. Workshop on Computer Architecture for Pattern Analysis and Machine Intelligence, Seattle, WA, 1987, pp. 137–144.

    Google Scholar 

  12. V. Cantoni, K. N. Matthews, P. Burt, H. Freeman, A. Terrano, and G. van der Wal, CAIPS-the CAIP advanced image processing system, CAIP-TR-072, pp. 1–39, CAIP Center, Rutgers University, 1988.

    Google Scholar 

  13. S. L. Tanimoto, A hierarchical cellular logic for pyramid computers, J. Parallel Distrib. Comput. 1, 105–132 (1984).

    Article  Google Scholar 

  14. E. W. Kent and S. L. Tanimoto, Hierarchical cellular logic and the PIPE processor: structural and functional correspondence, Proc. IEEE Computer Society Workshop on Computer Architecture for Pattern Analysis and Image Database, 1985, pp. 311–319.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 1994 Springer Science+Business Media New York

About this chapter

Cite this chapter

Cantoni, V., Ferretti, M. (1994). Pipeline Multiresolution Systems. In: Pyramidal Architectures for Computer Vision. Advances in Computer Vision and Machine Intelligence. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2413-7_6

Download citation

  • DOI: https://doi.org/10.1007/978-1-4615-2413-7_6

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-6023-0

  • Online ISBN: 978-1-4615-2413-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics