A maximum entropy Kalman filter for signal reconstruction

TitleA maximum entropy Kalman filter for signal reconstruction
Publication TypeConference Paper
Year of Publication1999
AuthorsDavid, A., and T. Aboulnasr
Conference NameCircuits and Systems, 1999. ISCAS '99. Proceedings of the 1999 IEEE International Symposium on
Pagination151 -154 vol.4
Date Publishedjul.
Keywords2D separable filter expansion, filtering theory, finite constraint bound, image reconstruction, image recovery, Kalman filters, matrix algebra, maximum entropy Kalman filter, maximum entropy methods, optimisation, optimization criterion, reconstructed pixels, signal reconstruction

In this paper, we propose a Maximum Entropy Kalman Filter (MEKF) and its application in image recovery. The proposed 2-D MEKF employs Maximum Entropy (ME) as its optimization criterion to identify the appropriate parameters of a standard Kalman filter. The strength of the ME based filters is due to the fact that these filters make no assumptions regarding the unobserved data, and avoid the over-smoothing that is associated with the Mean Square Error (MSE) based algorithms. Furthermore, we address the issues of ME 2-D separable filter expansion and the finite constraint bound on the reconstructed pixels


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