A new 2-D Kalman diagonal filtering scheme is developed for image restoration in this paper. 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. A dedicated VLSI array processor is proposed for high speed processing.

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