EDP Sciences
Free access
Volume 443, Number 3, December I 2005
Page(s) 1087 - 1093
Section Instruments, observational techniques, and data processing
DOI http://dx.doi.org/10.1051/0004-6361:20053398

A&A 443, 1087-1093 (2005)
DOI: 10.1051/0004-6361:20053398

Robust reconstruction from chopped and nodded images

F. Lenzen1, O. Scherzer1 and S. Schindler2

1  Institute of Computer Science, University of Innsbruck, Technikerstraße 21a, 6020 Innsbruck, Austria
    e-mail: Frank.Lenzen@uibk.ac.at
2  Institute for Astrophysics, University of Innsbruck, Technikerstraße 25, 6020 Innsbruck, Austria

(Received 10 May 2005 / Accepted 30 July 2005)

A well-known technique to reduce the influence of thermal and background noise in ground-based infrared imaging is chopping and nodding, where four different signals of the same object are recorded and from which the object is reconstructed numerically. Since noise in the data can severely affect the reconstruction, regularization algorithms have to be implemented. In this paper we propose to combine iterative reconstruction algorithms with robust statistical methods. Moreover, we study the use of multiple chopped data sets with different chopping amplitudes and the appropriate numerical reconstruction algorithm. Numerical simulations show the robustness of the proposed methods in dealing with noisy data.

Key words: methods: data analysis -- techniques: image processing -- infrared: general

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