Abstract
This paper presents a theoretical basis for a set of optimal filters for the reconstruction of piecewise-continuous one-dimensional signals, drawing from Bayesian networks and Kaiman filters. Results are presented for synthetic and real data, using both the optimal filters and a sub-optimal implementation. The results compare well with linear space invariant filtering or facet fitting approaches, and present a basis for the design of image restoration algorithms.
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© 1992 Springer-Verlag London Limited
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Dickson, J.W. (1992). A Step Towards Efficient Bayesian Signal Reconstruction. In: Hogg, D., Boyle, R. (eds) BMVC92. Springer, London. https://doi.org/10.1007/978-1-4471-3201-1_20
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DOI: https://doi.org/10.1007/978-1-4471-3201-1_20
Publisher Name: Springer, London
Print ISBN: 978-3-540-19777-5
Online ISBN: 978-1-4471-3201-1
eBook Packages: Springer Book Archive