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Parameterfree information-preserving surface restoration

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (1994) 801 LNCS 218-224
DOI: 10.1007/bfb0028355
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Abstract

In this paper we present an algorithm for parameterfree information-preserving surface restoration. The algorithm is designed for 2.5D and 3D surfaces. The basic idea is to extract noise and signal properties of the data simultaneously by variance-component estimation and use this information for filtering. The variance-component estimation delivers information on how to weigh the influence of the data dependent term and the stabilizing term in regularization techniques, and therefore no parameter which controls this relation has to be set by the user.

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Weidner, U. (1994). Parameterfree information-preserving surface restoration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 801 LNCS, pp. 218–224). Springer Verlag. https://doi.org/10.1007/bfb0028355

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