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This document discusses a new method for recursive least squares smoothing of noise in images using a two-dimensional Kalman filter. It critiques previous attempts to generalize the Kalman filter to two dimensions, demonstrating their lack of optimality, and proposes a model based on first-order difference equations that incorporates both horizontal and vertical correlations. The effectiveness of the proposed method is illustrated through experimental results on a noise-corrupted image.

Author

a.bbc

Language

EN