Share Email Print
cover

Proceedings Paper

Adaptive surface smoothing for enhancement of range data with multiple regularization parameters
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

This paper proposes an adaptive regularized noise smoothing algorithm for range images using the area decreasing flow method, which can preserve meaningful edges during the smoothing process. Adaptation is incorporated by adjusting the regularization parameter according to the results of surface curvature analysis. In general, range data includes mixed noise such as Gaussian or impulsive noise. Although non-adaptive version of regularized noise smoothing algorithm can easily reduce Gaussian noise, impulsive noise caused by random fluctuation of the sensor acquisition is not easy to be removed from observed range data. It is also difficult to remove noise near edge using the existing adaptive regularization algorithms. In order to cope with the problem, the second smoothness constraint is additionally incorporated into the existing regularization algorithm, which minimizes the difference between the median filtered data and the estimated data. As a result, the proposed algorithm can effectively remove the noise of dense range data while meaningful edge is well-preserved.

Paper Details

Date Published: 16 April 2004
PDF: 10 pages
Proc. SPIE 5302, Three-Dimensional Image Capture and Applications VI, (16 April 2004); doi: 10.1117/12.526435
Show Author Affiliations
Hyunjong Ki, Chung-Ang Univ. (South Korea)
Jeongho Shin, Chung-Ang Univ. (South Korea)
Joonki Paik, Chung-Ang Univ. (South Korea)


Published in SPIE Proceedings Vol. 5302:
Three-Dimensional Image Capture and Applications VI
Brian D. Corner; Peng Li; Roy P. Pargas, Editor(s)

© SPIE. Terms of Use
Back to Top