Paper
20 November 2001 Shape reconstruction from brightness functions
Richard J. Gardner, Peyman Milanfar
Author Affiliations +
Abstract
In this paper we address the problem of reconstructing the shape of a convex object from measurements of the area of its shadows in several directions. This type of very weak measurement is sometime referred to as the brightness function of the object, and may be observed in an imaging scenario by recording the total number of pixels where the object's image appears. These types of measurements, collected as a function of viewing angle, are also referred to as lightcurves in the astrophysics community, and are employed in estimating the shape of atmosphere less rotating bodies (e.g. asteroids). We address the problem of shape reconstruction from brightness functions by constructing a least-squares optimization framework for approximating the underlying shapes with polygons in 2-D, or polyhedra in 3-D, from noisy, and possibly sparse measurements of the brightness values.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard J. Gardner and Peyman Milanfar "Shape reconstruction from brightness functions", Proc. SPIE 4474, Advanced Signal Processing Algorithms, Architectures, and Implementations XI, (20 November 2001); https://doi.org/10.1117/12.448654
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Cited by 5 scholarly publications.
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KEYWORDS
Reconstruction algorithms

Inverse problems

Optical spheres

3D image reconstruction

3D metrology

Distance measurement

Astrophysics

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