Solving ill-posed Image Processing problems using Data Assimilation. Application to optical flow - Archive ouverte HAL Access content directly
Reports (Research Report) Year : 2008

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.
Fichier principal
Vignette du fichier
RR-6477.pdf (632.12 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

inria-00264661 , version 1 (17-03-2008)
inria-00264661 , version 2 (18-03-2008)
inria-00264661 , version 3 (20-03-2008)
inria-00264661 , version 4 (19-07-2008)

Identifiers

  • HAL Id : inria-00264661 , version 4

Cite

Dominique Béréziat, Isabelle L. Herlin. Solving ill-posed Image Processing problems using Data Assimilation. Application to optical flow. [Research Report] RR-6477, INRIA. 2008, pp.15. ⟨inria-00264661v4⟩
238 View
347 Download

Share

Gmail Facebook Twitter LinkedIn More