Abstract
This paper presents both standard and adaptive versions of regularized surface smoothing algorithms for 3D image enhancement. We incorporated both area decreasing flow and the median constraint as multiple regularization functionals. The corresponding regularization parameters adaptively changes according to the local curvature value. The combination of area decreasing flow and the median constraint can efficiently remove various types of noise, such as Gaussian, impulsive, or mixed types. The adaptive version of the proposed regularized smoothing algorithm changes regularization parameters based on local curvature for preserving local edges and creases that reflects important surface information in 3D data. In addition to the theoretical expansion, experimental results show that the proposed algorithms can significantly enhance 3D data acquired by both laser range sensors and disparity maps from stereo images.
This work was supported in part by Korean Ministry of Science and Technology under the National Research Lab. Project, in part by Korean Ministry of Education under Brain Korea 21 Project, and in part by grant No.R08-2004-000-10626-0 from the Basic Research Program of the Korea Science & Engineering Foundation.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Blake, A., Zisserman, A.: Visual Reconstruction. MIT Press, Cambridge (1987)
Geman, S., Geman, D.: Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images. IEEE Trans. Pattern Analysis, Machine Intelligence 6, 721–741 (1984)
Terzopoulos, D.: The computation of visual surface representations. IEEE Trans. Pattern Analysis, Machine Intelligence 10, 417–438 (1988)
Gokmen, M., Li, C.-C.: Edge detection and surface reconstruction using refined regularization. IEEE Trans. Pattern Analysis, Machine Intelligence 15, 492–499 (1993)
Katsaggelos, A.K., Biemond, J., Schafer, R.W., Mersereau, R.M.: A regularized iterative image restoration algorithms. IEEE Trans. Signal Processing 39, 914–929 (1991)
Sinha, S.S., Schunck, B.G.: A two-stage algorithm for discontinuity-preserving surface reconstruction. IEEE Trans. Pattern Analysis, Machine Intelligence 14, 36–55 (1992)
Umasuthan, M., Wallace, A.M.: Outlier removal and discontinuity preserving smoothing of range data. IEE Proc.-Vis. Image Signal Process 143, 191–200 (1996)
Hoover, A.: The Space Envelope Representation for 3D Scenes, PhD thesis, Department of Computer Science and Engineering, University of South Florida (1996)
Carmo, M.D.: Differential geometry of curves and surfaces. Prentice Hall, Englewood Cliffs (1976)
June, H.Y., David, M.C.: Discontinuity-preserving and viewpoint invariant reconstruction of visible surface using a first order regularization. IEEE Trans. Pattern Analysis, Machine Intelligence 17 (1995)
Stevenson, R.L., Delp, E.J.: Viewpoint invariant recovery of visual surface from sparse data. IEEE Trans. Pattern Analysis, Machine Intelligence 14, 897–909 (1992)
Trucco, E., Verri, A.: Introductory Techniques for 3-D Computer Vision. Prentice-Hall, Englewood Cliffs (1998)
Shin, J.H., Sun, Y., Joung, W.C., Paik, J.K., Abidi, M.A.: Regularized noise smoothing of dense range image using directional Laplacian operators. In: Proc. SPIE Three-Dimensional Image Capture and Applications IV, vol. 4298, pp. 119–126 (2001)
Sun, Y., Paik, J.K., Price, J.R., Abidi, M.A.: Dense range image smoothing using adaptive regularization. In: Proc. 2000 Int. Conf. Image Processing, vol. 2, pp. 10–13 (2000)
Ki, H., Shin, J., Paik, J.: Regularized surface smoothing for enhancement of range data. Proc. IEEK 26, 1903–1906 (2003) (in Korean)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ki, H., Shin, J., Jung, J., Lee, S., Paik, J. (2004). Surface Smoothing for Enhancement of 3D Data Using Curvature-Based Adaptive Regularization. In: Klette, R., Žunić, J. (eds) Combinatorial Image Analysis. IWCIA 2004. Lecture Notes in Computer Science, vol 3322. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30503-3_35
Download citation
DOI: https://doi.org/10.1007/978-3-540-30503-3_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23942-0
Online ISBN: 978-3-540-30503-3
eBook Packages: Computer ScienceComputer Science (R0)