Solving ill-posed Image Processing problems using Data Assimilation. Application to optical flow

Abstract : Data Assimilation is a methodological framework used in environmental sciences to perform forecasts with complex systems such as meteorological, oceanographic and air quality models. Data Assimilation requires the resolution of a system with three components: one describing the temporal evolution of the state vector, one coupling the observations and the state vector, and one defining the initial condition. In this article we use this mathematical framework to study a class of ill-posed Image Processing problems, which are usually solved using regularization techniques. To this end, the ill-posed problem is formulated according to the three-component system of the Data Assimilation framework. To illustrate the method, an application for computing optical flow is described.
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Rapport
[Research Report] RR-6477, INRIA. 2008, pp.15
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https://hal.inria.fr/inria-00264661
Contributeur : Dominique Béréziat <>
Soumis le : samedi 19 juillet 2008 - 00:13:49
Dernière modification le : jeudi 11 janvier 2018 - 06:14:33
Document(s) archivé(s) le : samedi 26 novembre 2016 - 00:22:08

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  • HAL Id : inria-00264661, version 4

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Dominique Béréziat, Isabelle Herlin. Solving ill-posed Image Processing problems using Data Assimilation. Application to optical flow. [Research Report] RR-6477, INRIA. 2008, pp.15. 〈inria-00264661v4〉

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