Adaptive surface smoothing for enhancement of range data with multiple regularization parameters

Hyunjong Ki; Jeongho Shin; Joonki Paik

doi:10.1117/12.526435

16 April 2004 Adaptive surface smoothing for enhancement of range data with multiple regularization parameters

Hyunjong Ki, Jeongho Shin, Joonki Paik

Proceedings Volume 5302, Three-Dimensional Image Capture and Applications VI; (2004) https://doi.org/10.1117/12.526435
Event: Electronic Imaging 2004, 2004, San Jose, California, United States

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.

Citation Download Citation

Hyunjong Ki, Jeongho Shin, and Joonki Paik "Adaptive surface smoothing for enhancement of range data with multiple regularization parameters", Proc. SPIE 5302, Three-Dimensional Image Capture and Applications VI, (16 April 2004); https://doi.org/10.1117/12.526435

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KEYWORDS

Digital filtering

Smoothing

Image processing

Signal to noise ratio

3D image processing

Scanners

Gaussian filters

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