Some Estimation and Restoration Techniques for Statistical Image Analysis

Archer, Graeme Ernest Barclay (1994) Some Estimation and Restoration Techniques for Statistical Image Analysis. PhD thesis, University of Glasgow.

Full text available as:
Download (13MB) | Preview


This thesis is concerned with statistical image analysis: the estimation of parameters within image models, and how to produce restorations of degraded scenes which are the most probable given the parameter estimates and the data. We develop algorithms for estimation within hierarchical and empirical Bayesian models, and compare results with non-Bayesian methods. The empirical behaviour of parameter estimates under different algorithms are studied in a simulation exercise and compared with their theoretical behaviour. We sample realisations from Markov random fields using the Metropolis algorithm, and propose a resampling technique to assess convergence. An alternative to the EM algorithm (EMA), the Image Space Reconstruction algorithm (ISRA), is extended and compared with the EMA. A technique for increasing the rate of ISRA-convergence is investigated. Finally, an adaption of a method to prevent over-smoothing of image discontinuities is fully automated. The effect of user-supplied parameter values on the image restoration quality is investigated via a simulation study; the effects are found to be negligible.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Additional Information: Adviser: Michael Titterington
Keywords: Statistics
Date of Award: 1994
Depositing User: Enlighten Team
Unique ID: glathesis:1994-76438
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 19 Nov 2019 14:20
Last Modified: 19 Nov 2019 14:20

Actions (login required)

View Item View Item


Downloads per month over past year