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Estimation of images modeled by a two-dimensional separable autoegressive process

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1 Author(s)
Katayama, T. ; Kyoto University, Kyoto, Japan

This note considers the estimation of two-dimensional images that may be modeled by a separable autoregressive process. We first derive a one-dimensional vector stochastic model with multiple delays for images; the one-dimensional vector model is further decomposed into a set of nearly independent equations using the matrix factorization theorem and the orthogonal sine transform [10]. Then, applying the kalman filter, the approximate feasible estimation algorithm is obtained.

Published in:

Automatic Control, IEEE Transactions on  (Volume:25 ,  Issue: 6 )