Real Time Pyramid Transform Architecture

Gooitzen S. van der Wal; Joseph O . Sinniger

doi:10.1117/12.950814

11 December 1985 Real Time Pyramid Transform Architecture

Gooitzen S. van der Wal, Joseph O . Sinniger

Proceedings Volume 0579, Intelligent Robots and Computer Vision IV; (1985) https://doi.org/10.1117/12.950814
Event: 1985 Cambridge Symposium, 1985, Cambridge, United States

Abstract

This paper describes an architecture for creating pyramid transforms of real time video images. A powerful preprocessor can be designed with this architecture by representing the image data in a form most suitable for the application. The Burt pyramid algorithm [1], an efficient method for transforming video images into hierarchical representation, is an example of an effective transform. A programmable version of such a preprocessor, occupying two Multibus* boards, was built at low cost using available hardware. This unit can perform the basic pyramid trans-form on 256 x 240 images in real time. More complex and/or multiple transforms can be performed at reduced data rate by passing data through the unit several times, or can be performed in real time by passing data through multiple units. Because the preprocessor is programmable, the system is easily configured to perform several different pyramid transforms, or the appropriate inverse transforms. Algorithms can be developed to reduce edge effects by modifying the edges of the image before applying the transform. The preprocessor can be programmed to insert time delays into the system, which is useful in the display of the results. Image processing system, design can be simplified by using the preprocessor to significantly reduce the computational requirements of the main processor. The proposed architecture, suitable for system integration, could lead to the availability of low cost, efficient image processing systems.

Citation Download Citation

Gooitzen S. van der Wal and Joseph O . Sinniger "Real Time Pyramid Transform Architecture", Proc. SPIE 0579, Intelligent Robots and Computer Vision IV, (11 December 1985); https://doi.org/10.1117/12.950814

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