@inproceedings{7227ee34f3da482da84d9d8a905be20c,
title = "A Kalman filtering approach to stochastic tomography",
abstract = "An isotropic random field is expanded into its circular harmonics. Computation of its Radon transform is equivalent to computation of the nth-order Abel transform of the nth order circular harmonic. A state-space model is fitted to the Abel transform of each order and augmented with a state-space model describing the random field circular harmonic. The latter is derived using backward Markovianization of a two-point boundary value model. The tomographic problem of computing the inverse Radon transform is then solved by using a bank of Kalman filters to estimate each random field harmonic separately. Combining these gives the linear least-squares estimate of the random field. The authors also consider a simpler Wiener-process model of the circular harmonics.",
author = "Luo, {Der Shan} and Yagle, {Andrew E.}",
note = "Copyright: Copyright 2004 Elsevier B.V., All rights reserved.; Proceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing - ICASSP 91 ; Conference date: 14-05-1991 Through 17-05-1991",
year = "1991",
language = "English (US)",
isbn = "078030033",
series = "Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing",
publisher = "Publ by IEEE",
pages = "2589--2592",
editor = "Anon",
booktitle = "Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing",
}