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Proceedings Paper

Resolution enhancement of blurred star field images by maximally sparse restoration
Author(s): Brian D. Jeffs; Metin Gunsay; John Dougal
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Paper Abstract

In this paper we address the problem of removing blur from, or sharpening, astronomical star field intensity images. A new image restoration algorithm is introduced which recovers image detail using a constrained optimization theoretic approach. Ideal star images may be modeled as a few point sources in a uniform background. It is therefore argued that a direct measure of image sparseness is the appropriate optimization criterion for deconvolving the image blurring function. A sparseness criterion based on the lp quasinorm is presented and algorithms for sparse reconstruction are described. Synthetic and actual star image reconstruction examples are presented which demonstrate the algorithm's superior performance as compared with the CLEAN algorithm, a standard star field deconvolution method.

Paper Details

Date Published: 1 December 1991
PDF: 11 pages
Proc. SPIE 1567, Applications of Digital Image Processing XIV, (1 December 1991); doi: 10.1117/12.50842
Show Author Affiliations
Brian D. Jeffs, Brigham Young Univ. (United States)
Metin Gunsay, Brigham Young Univ. (United States)
John Dougal, Brigham Young Univ. (United States)

Published in SPIE Proceedings Vol. 1567:
Applications of Digital Image Processing XIV
Andrew G. Tescher, Editor(s)

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