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Proceedings Paper

Wavelet discretization methods for surface estimation and reconstruction
Author(s): Wayne M. Lawton
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Paper Abstract

Orthonormal wavelet bases recently constructed by Ingrid Daubechies provide an efficient means of discretely representing curves and surfaces for computer vision and graphics. Advantages of this representation implied by the scaling, finite extent, and vanishing moment properties of the basis functions include multi-level algorithms, spatially adaptive resolution, and high order approximations with respect to Sobelev norms. This paper reviews the construction of these wavelet bases and describes wavelet discretization methods. It discusses two specific applications to surface estimation and reconstruction and presents preliminary numerical results.

Paper Details

Date Published: 1 August 1990
PDF: 12 pages
Proc. SPIE 1251, Curves and Surfaces in Computer Vision and Graphics, (1 August 1990); doi: 10.1117/12.19750
Show Author Affiliations
Wayne M. Lawton, AWARE, Inc. (United States)

Published in SPIE Proceedings Vol. 1251:
Curves and Surfaces in Computer Vision and Graphics
Leonard A. Ferrari; Rui J. P. de Figueiredo, Editor(s)

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