A two-stage algorithm for discontinuity-preserving surfacereconstruction
Sinha, S.S.
Schunck, B.G.
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Jan 1992
Volume: 14,
Issue: 1
On page(s): 36-55
ISSN: 0162-8828
References Cited: 61
CODEN: ITPIDJ
INSPEC Accession Number: 4118904
Digital Object Identifier: 10.1109/34.107012
Current Version Published: 2002-08-06
Abstract
A two-stage algorithm for visual surface reconstruction from
scattered data while preserving discontinuities is presented. The first
stage consists of a robust local approximation algorithm (the moving
least median of squares (MLMS) of error) to clean the data and create a
grid from the original scattered data points. This process is
discontinuity preserving. The second stage introduces a weighted bicubic
spline (WBS) as a surface descriptor. The WBS has a factor in the
regularizing term that adapts the behavior of the spline across
discontinuities. The weighted bicubic approximating spline can
approximate data with step discontinuities with no discernible
distortion in the approximating surface. The combination of robust
surface fitting and WBSs removes outliers and reduces Gaussian noise.
Either stage by itself would not effectively remove both kinds of noise.
Experimental results with the two-stage algorithm are presented
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