Optimization of regularization operators for adaptive least-squares image restoration

Bernhard O. Bundschuh

doi:10.1117/12.199617

19 January 1995 Optimization of regularization operators for adaptive least-squares image restoration

Bernhard O. Bundschuh

Proceedings Volume 2363, 5th International Workshop on Digital Image Processing and Computer Graphics (DIP-94); (1995) https://doi.org/10.1117/12.199617
Event: Digital Image Processing and Computer Graphics: Fifth International Workshop, 1994, Samara, Russian Federation

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).

Citation Download Citation

Bernhard O. Bundschuh "Optimization of regularization operators for adaptive least-squares image restoration", Proc. SPIE 2363, 5th International Workshop on Digital Image Processing and Computer Graphics (DIP-94), (19 January 1995); https://doi.org/10.1117/12.199617

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