Resolution enhancement of blurred star field images by maximally sparse restoration

Brian D. Jeffs; Metin Gunsay; John Dougal

doi:10.1117/12.50842

1 December 1991 Resolution enhancement of blurred star field images by maximally sparse restoration

Brian D. Jeffs, Metin Gunsay, John Dougal

Proceedings Volume 1567, Applications of Digital Image Processing XIV; (1991) https://doi.org/10.1117/12.50842
Event: San Diego, '91, 1991, San Diego, CA, United States

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.

Citation Download Citation

Brian D. Jeffs, Metin Gunsay, and John Dougal "Resolution enhancement of blurred star field images by maximally sparse restoration", Proc. SPIE 1567, Applications of Digital Image Processing XIV, (1 December 1991); https://doi.org/10.1117/12.50842

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