Prediction Techniques for Dynamic Imaging with Online Primal–Dual Methods
Pages 1109 - 1134
Abstract
Online optimisation facilitates the solution of dynamic inverse problems, such as image stabilisation, fluid flow monitoring, and dynamic medical imaging. In this paper, we improve upon previous work on predictive online primal–dual methods on two fronts. Firstly, we provide a more concise analysis that symmetrises previously unsymmetric regret bounds, and relaxes previous restrictive conditions on the dual predictor. Secondly, based on the latter, we develop several improved dual predictors. We numerically demonstrate their efficacy in image stabilisation and dynamic positron emission tomography.
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Kluwer Academic Publishers
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Publication History
Published: 10 October 2024
Accepted: 10 September 2024
Received: 03 May 2024
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