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Proceedings Paper

High Speed Kalman Filtering For Image Restoration
Author(s): Jin Yun Zhang; Willem Steenaart
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Paper Abstract

In this paper a fast Kalman filter is developed for digital image restoration. Optimal restoration schemes for two-dimensional images degraded by both blur and noise create dimensionality problems which, in turn, lead to intensive computation. When the original image model and the degradation model are both represented by Roesser's 2-D SISO state-space models, a simple composite dynamic structure based on a cascade technique is obtained. From this composite model, the Kalman filtering equations are established by defining a proper state vector. The speed of the recursive estimation procedure can be improved by processing the image along the diagonal direction. Furthermore, a dedicated VLSI array processor for high speed processing is proposed.

Paper Details

Date Published: 1 November 1989
PDF: 11 pages
Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); doi: 10.1117/12.970025
Show Author Affiliations
Jin Yun Zhang, University of Ottawa (Canada)
Willem Steenaart, University of Ottawa (Canada)


Published in SPIE Proceedings Vol. 1199:
Visual Communications and Image Processing IV
William A. Pearlman, Editor(s)

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