Point-spread function reconstruction in ground-based astronomy by l 1-lp model

Raymond H. CHAN, Xiaoming YUAN*, Wenxing ZHANG

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

11 Citations (Scopus)

Abstract

In ground-based astronomy, images of objects in outer space are acquired via ground-based telescopes. However, the imaging system is generally interfered by atmospheric turbulence, and hence images so acquired are blurred with unknown point-spread function (PSF). To restore the observed images, the wavefront of light at the telescope's aperture is utilized to derive the PSF. A model with the Tikhonov regularization has been proposed to find the high-resolution phase gradients by solving a least-squares system. Here we propose the l1-lp (p = 1, 2) model for reconstructing the phase gradients. This model can provide sharper edges in the gradients while removing noise. The minimization models can easily be solved by the Douglas-Rachford alternating direction method of a multiplier, and the convergence rate is readily established. Numerical results are given to illustrate that the model can give better phase gradients and hence a more accurate PSF. As a result, the restored images are much more accurate when compared to the traditional Tikhonov regularization model.

Original languageEnglish
Pages (from-to)2263-2271
Number of pages9
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Volume29
Issue number11
Early online date9 Oct 2012
DOIs
Publication statusPublished - Nov 2012
Externally publishedYes

Funding

The first author is supported in part by Hong Kong Research Grants Council (HKRGC) Grant No. CUHK400510 and CUHK Direct Allocation Grant 2060408, and the second author is supported by HKRGC Grant No. HKBU203311.

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