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A very fast Kalman filter for image restoration

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2 Author(s)
Zhang, J.Y. ; Dept. of Electr. Eng., Ottawa Univ., Ont., Canada ; Steenaart, W.

The application of 2-D Kalman filtering to the restoration of images degraded by linear space invariant blur and additive white Gaussian noise is described. R.P. Roesser's 2-D local state space model (1975) is used to represent the image process and the blur process. As a result, a simple procedure for establishing the Kalman filter equations is obtained. This scalar filtering algorithm provides a computationally feasible procedure for the restoration of large images. To speed up the Kalman filtering procedure, a VLSI systolic array structure is presented. For higher speed and higher utilization of this processor, a diagonal scanning method is suggested. The filter scheme can be easily extended to the causal image model and the causal blur model with nonsymmetric half-plane support

Published in:

Circuits and Systems, 1990., IEEE International Symposium on

Date of Conference:

1-3 May 1990

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