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Journal of Electronic Imaging

Eigenspace-based surface completeness
Author(s): Hongchuan Yu; Yipeng Qin; Jian J. Zhang
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Paper Abstract

We present a surface completeness algorithm that is capable of denoising, removing outliers, and filling in missing patches on point clouds or surfaces. The main advantages of the proposed algorithm include its ability to remove outliers while preserving the details and ability to recover large missing patches. Additionally, our algorithm is a global method, whereby linear programming results are applied to a global optimization problem. This is advantageous because it yields a sparse solution and avoids local minima. Experiments further demonstrate the effectiveness of our algorithm through applications to point clouds where noise, outliers, and large missing patches exist.

Paper Details

Date Published: 28 April 2015
PDF: 9 pages
J. Electron. Imaging. 24(2) 023037 doi: 10.1117/1.JEI.24.2.023037
Published in: Journal of Electronic Imaging Volume 24, Issue 2
Show Author Affiliations
Hongchuan Yu, Bournemouth Univ. (United Kingdom)
Yipeng Qin, Bournemouth Univ. (United Kingdom)
Jian J. Zhang, Bournemouth Univ. (United Kingdom)

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