Denoising point sets via L-0 minimization Academic Article

abstract

• 2015 Elsevier B.V. All rights reserved. We present an anisotropic point cloud denoising method using L0 minimization. The L0 norm directly measures the sparsity of a solution, and we observe that many common objects can be defined as piecewise smooth surfaces with a small number of features. Hence, we demonstrate how to apply an L0 optimization directly to point clouds, which produces sparser solutions and sharper surfaces than either the L1 or L2 norm. Our method can faithfully recover sharp features while at the same time smoothing the remaining regions even in the presence of large amounts of noise.

authors

• Schaefer, Scott

published proceedings

• COMPUTER AIDED GEOMETRIC DESIGN

author list (cited authors)

• Sun, Y., Schaefer, S., & Wang, W.

citation count

• 95

complete list of authors

• Sun, Yujing||Schaefer, Scott||Wang, Wenping

publication date

• May 2015

publisher

• Elsevier  Publisher

published in

• Computer Aided Geometric Design  Journal

keywords

• Denoising
• L-0 Minimization
• L-0 Sparsity
• Point Set

Digital Object Identifier (DOI)

• 10.1016/j.cagd.2015.03.011

start page

• 2

end page

• 15

volume

• 35-36

URL

• http://dx.doi.org/10.1016/j.cagd.2015.03.011