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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: James C. Wyant
  • Vol. 47, Iss. 12 — Apr. 20, 2008
  • pp: 2091–2097

Shape reconstruction from gradient data

Svenja Ettl, Jürgen Kaminski, Markus C. Knauer, and Gerd Häusler  »View Author Affiliations


Applied Optics, Vol. 47, Issue 12, pp. 2091-2097 (2008)
http://dx.doi.org/10.1364/AO.47.002091


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Abstract

We present a generalized method for reconstructing the shape of an object from measured gradient data. A certain class of optical sensors does not measure the shape of an object but rather its local slope. These sensors display several advantages, including high information efficiency, sensitivity, and robustness. For many applications, however, it is necessary to acquire the shape, which must be calculated from the slopes by numerical integration. Existing integration techniques show drawbacks that render them unusable in many cases. Our method is based on an approximation employing radial basis functions. It can be applied to irregularly sampled, noisy, and incomplete data, and it reconstructs surfaces both locally and globally with high accuracy.

© 2008 Optical Society of America

OCIS Codes
(000.4430) General : Numerical approximation and analysis
(120.0120) Instrumentation, measurement, and metrology : Instrumentation, measurement, and metrology
(120.3940) Instrumentation, measurement, and metrology : Metrology
(120.6650) Instrumentation, measurement, and metrology : Surface measurements, figure
(150.6910) Machine vision : Three-dimensional sensing

ToC Category:
Instrumentation, Measurement, and Metrology

History
Original Manuscript: October 24, 2007
Revised Manuscript: January 30, 2008
Manuscript Accepted: February 4, 2008
Published: April 16, 2008

Citation
Svenja Ettl, Jürgen Kaminski, Markus C. Knauer, and Gerd Häusler, "Shape reconstruction from gradient data," Appl. Opt. 47, 2091-2097 (2008)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-47-12-2091


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