Shape reconstruction from gradient data

Details Shape reconstruction from gradient data Shape reconstruction from gradient data

2007-10-23

arxiv.org/abs/0710.4278v1

Physics

Optics

16 pages, 5 figures, zip-file, submitted to Applied Optics

Scientific paper

10.1364/AO.47.002091

We present a novel 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 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 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.

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