Statistics – Computation
Scientific paper
Jul 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004aspc..314..107w&link_type=abstract
Astronomical Data Analysis Software and Systems (ADASS) XIII, Proceedings of the conference held 12-15 October, 2003 in Strasbou
Statistics
Computation
Scientific paper
High-resolution astronomical images can be reconstructed from several blurred and noisy low-resolution images using a computational process known as superresolution reconstruction. Superresolution reconstruction is closely related to image deconvolution, except that the low-resolution images are not registered and their relative translations and rotations must be estimated in the process. The novelty of our approach to the superresolution problem is the use of wavelets and related multiresolution methods within an expectation-maximization reconstruction process to improve the accuracy and visual quality of the reconstructed image. Simulations demonstrate the effectiveness of the proposed method, including its ability to distinguish between tightly grouped stars with a small set of observations.
Jermyn Ian
Nowak Robert D.
Willett Rebecca M.
Zerubia Josiane
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