A unified approach for hierarchical imaging based on jointhypothesis testing and parameter estimation
Roysam, B.; Miller, M.I.
Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on
Volume , Issue , 23-26 May 1989 Page(s):1779 - 1782 vol.3
Digital Object Identifier 10.1109/ICASSP.1989.266795
Summary:The authors present a single formulation for constrained imaging
that fuses the problem of joint estimation of the continuous parameters
using MAP (maximum a posteriori) and conditional-mean estimators with
that of performing generalized Bayes hypothesis testing for the symbolic
imaging variables. Coupling this with recent results on representing
regular grammars via Gibbs' distributions makes it possible to
incorporate into a single hierarchical framework the stochastic
constraints relevant to continuous-valued parameters as well as
language-theoretic constraints on the symbolic variables. The authors
also present a method for performing the required computations on a
massively parallel architecture, which makes it possible to update every
variable at every level in the hierarchy in parallel. The conclusions
obtained are supported with results for a Poisson imaging problem
computed on a DAP-500 massively parallel processor with 1024 processing
elements
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