Abstract
In a number of astrophysical applications one tries to determine the two-dimensional or three-dimensional structure of an object from a time series of measurements. While most methods used for reconstruction assume that the object is static, the data are often acquired over a time interval during which the object may change significantly. This problem can be addressed with time-dependent reconstruction methods such as Kalman filtering, which models the temporal evolution of the unknown object as a random walk that may or may not have a deterministic component. Time-dependent reconstructions of a hydrodynamic simulation from its line-integral projections are presented. In these examples standard reconstructions based on the static assumption are poor, while good quality reconstructions are obtained from a regularized Kalman estimate. Implications for various astrophysical applications, including tomography of the solar corona and radio aperture synthesis, are discussed.
Original language | English (US) |
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Pages (from-to) | L197-L200 |
Journal | Astrophysical Journal |
Volume | 635 |
Issue number | 2 II |
DOIs | |
State | Published - Dec 20 2005 |
Keywords
- Methods: statistical
- Techniques: image processing
- Techniques: interferometric
ASJC Scopus subject areas
- Astronomy and Astrophysics
- Space and Planetary Science