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Proceedings Paper

Optimization of regularization operators for adaptive least-squares image restoration
Author(s): Bernhard O. Bundschuh
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Paper Abstract

This paper presents regularized least squares algorithms for the restoration and reconstruction of images. Whitening filters of short length are derived formally as optimal regularization operators. Adaptive versions of the algorithms are developed by matching a weighting function to the particular regularization function. The adaptive regularization leads to proper noise suppression as well as to enhanced resolution of discontinuities. The application focuses on the restoration of images recorded by the Hubble Space Telescope (HST).

Paper Details

Date Published: 19 January 1995
PDF: 8 pages
Proc. SPIE 2363, 5th International Workshop on Digital Image Processing and Computer Graphics (DIP-94), (19 January 1995); doi: 10.1117/12.199617
Show Author Affiliations
Bernhard O. Bundschuh, Fachhochschule Merseburg (Germany)


Published in SPIE Proceedings Vol. 2363:
5th International Workshop on Digital Image Processing and Computer Graphics (DIP-94)
Nikolai A. Kuznetsov; Victor A. Soifer, Editor(s)

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