×

Continuous level anisotropic diffusion for noise removal. (English) Zbl 1252.94029

Summary: We present a new approach to anisotropic diffusion and noise removal. Several functionals are introduced to a variational model. The diffusion behavior is governed by a nonlinear partial differential equation. A dynamic threshold function plays an important role in the continuous level anisotropic diffusion and a related optimization problem is presented. The noise can be removed while the edge well preserved. Multi-level noise or multi-level edge can be handled automatically. Finally, the accuracy and efficiency of the proposed method are verified by several numerical experiments.

MSC:

94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
Full Text: DOI

References:

[1] El-Fallah, A. I.; Ford, G. E., Mean curvature evolution and surface area scaling in image filtering, IEEE Trans. Image Process., 6, 5, 750-753 (2002)
[2] Perona, P.; Malik, J., Scale-space and edge detection using anisotropic diffusion, IEEE Trans. Pattern Anal. Machine Intelligence, 12, 7, 629-639 (1990)
[3] Yezzi, A., Modified curvature motion for image smoothing and enhancement, IEEE Transactions on Image Processing, 7, 3, 345-352 (2002)
[4] L.I. Rudin, S. Osher. Total variation based image restoration with free local constraints. in: IEEE Int. Conf. Image Process., 1994. Proceedings. ICIP-94., pp. 31-35, 1994.; L.I. Rudin, S. Osher. Total variation based image restoration with free local constraints. in: IEEE Int. Conf. Image Process., 1994. Proceedings. ICIP-94., pp. 31-35, 1994.
[5] Rudin, L. I.; Osher, S.; Fatemi, E., Nonlinear total variation based noise removal algorithms, Physica D: Nonlinear Phenomena, 60, 1-4, 259-268 (1992) · Zbl 0780.49028
[6] Moroney, T. J.; Turner, I. W., A finite volume method based on radial basis functions for two-dimensional nonlinear diffusion equations, Appl. Math. Model., 30, 10, 1118-1133 (2006) · Zbl 1099.65114
[7] A. Kuijper, p-Laplacian driven image processing. in: IEEE Int. Conf. Image Process., 2007. ICIP 2007., vol. 5, pp. 257-260, 2007.; A. Kuijper, p-Laplacian driven image processing. in: IEEE Int. Conf. Image Process., 2007. ICIP 2007., vol. 5, pp. 257-260, 2007.
[8] Catté, F.; Lions, P. L.; Morel, J. M.; Coll, T., Image selective smoothing and edge detection by nonlinear diffusion, SIAM J. Numer. Anal., 29, 1, 182-193 (1992) · Zbl 0746.65091
[9] Lysaker, M.; Lundervold, A.; Tai, X. C., Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time, IEEE Trans. Image Process., 12, 12, 1579-1590 (2004) · Zbl 1286.94020
[10] You, Y. L.; Kaveh, M., Fourth-order partial differential equations for noise removal, IEEE Trans. Image Process., 9, 10, 1723-1730 (2002) · Zbl 0962.94011
[11] Malladi, R.; Sethian, J. A., A unified approach to noise removal, image enhancement, and shape recovery, IEEE Trans. Image Process., 5, 11, 1554-1568 (2002)
[12] Lee, S. H.; Seo, J. K., Noise removal with Gauss curvature-driven diffusion, IEEE Trans. Image Process., 14, 7, 904-909 (2005)
[13] Whitaker, R. T.; Pizer, S. M., A multi-scale approach to nonuniform diffusion, CVGIP Image Understand., 57 (1993), 99-99
[14] Koenderink, J. J., The structure of images, Biol. Cybernetics, 50, 5, 363-370 (1984) · Zbl 0537.92011
[15] A.P. Witkin. Scale-space filtering. in: Proc. 8th Int. Joint Conference Artificial Intelligence, vol. 2, pages 1019-1022. Morgan Kaufmann Publishers Inc., 1983.; A.P. Witkin. Scale-space filtering. in: Proc. 8th Int. Joint Conference Artificial Intelligence, vol. 2, pages 1019-1022. Morgan Kaufmann Publishers Inc., 1983.
[16] Aubert, G.; Kornprobst, P., Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (2006), Springer-Verlag: Springer-Verlag New York Inc · Zbl 1110.35001
[17] Chambolle, A.; Lions, P. L., Image recovery via Total Variation minimization and related problems, Numerische Mathematik, 76, 2, 167-188 (1997) · Zbl 0874.68299
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.