Tomographic reconstruction from noisy data
A generalised maximum entropy based approach to noisy inverse problems such as the Abel problem, tomography, or deconvolution is discussed and reviewed. Unlike the more traditional regularisation approach, in the method discussed here, each unknown parameter (signal and noise) is redefined as a proper probability distribution within a certain pre-specified support. Then the joint entropies of both the noise and signal probabilities are maximised subject to the observed data. We use this method for tomographic reconstruction of the soft X-ray emissivity of hot fusion plasma.
Bibliographic Reference: An article published in: Bayesian inference and maximum entropy methods in science and engineering, 21st International Workshop, edited by R.L.Fry, American Institute of Physics, 2002, pp.248-258.
ISBN: ISBN: 0-7354-0063-6
Record Number: 200214940 / Last updated on: 2002-07-08
Original language: en
Available languages: en