Abstract
A region-based variational model for color image segmentation is proposed using the chromaticity-brightness decomposition. By this decomposition, we extend the Wasserstein distance based method to color images. The chromaticity term of the proposed functional follows the data term of the color Chan-Vese model with constraint on unit sphere, and the brightness term is formulated by the Wasserstein distance between the computed probability density function in the local windows (e.g. 3 by 3 or 5 by 5 window) and its estimated counterparts in classified regions. Experimental results on synthetic and real color images show that the proposed method performs well for the segmentation of different image regions.
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References
Chan, T.F., Vese, L.A.: Active contours without edges. IEEE Trans. Image Processing 10(2), 266–277 (2001)
Chan, T.F., Sandberg, B.Y., Vese, L.A.: Active contours without edges for vector-valued images. Jour. Visual Comm. Image Represent. 11(2), 130–141 (2000)
Ni, K., Bresson, X., Chan, T.F., Esedoglu, S.: Local histogram based segmentation using Wasserstein distance. UCLA CAM reports 08-47, USA (2008)
Chan, T.F., Esedoglu, S., Ni, K.: Histogram Based Segmentation Using Wasserstein Distances. In: Sgallari, F., Murli, A., Paragios, N. (eds.) SSVM 2007. LNCS, vol. 4485, pp. 697–708. Springer, Heidelberg (2007)
Gonzalez, R., Wood, R.: Digital image processing, 2nd edn. Publishing House of Electronics Industry, Beijing (2002)
Chan, T.F., Kang, S.H., Shen, J.: Total variation denoising and enhancement of color images based on the CB and HSV color models. Jour. Visual Comm. Image Represent. 12(4), 422–435 (2001)
Kang, S.H., March, R.: Variational models for image colorization via chromaticity and brightness decomposition. IEEE Trans. Image Processing 16(9), 2251–2261 (2007)
Caselles, V., Lions, P., Morel, J., Coll, T.: Geometry and color in natural images. Jour. Math. Imag. Vis. 16(2), 89–105 (2002)
Maenpaa, T., Pietikainen, M.: Classification with color and texture: jointly or separately. Pattern Recogn. 37(8), 1629–1640 (2004)
Villani, C.: Topics in optimal transportation. Graduate students in Mathematics, vol. 58. American Mathematical Society, Providence (2003)
Bresson, X., Esedoglu, S., Vandergheynst, P., Thiran, J., Osher, S.: Fast global minimization of the active contour/snake model. Jour. Math. Imag. Vis. 28(2), 151–167 (2007)
Mory, B., Ardon, R.: Fuzzy region competition: A convex two-phase segmentation framework. In: Sgallari, F., Murli, A., Paragios, N. (eds.) SSVM 2007. LNCS, vol. 4485, pp. 214–226. Springer, Heidelberg (2007)
Nikolova, M., Esedoglu, S., Chan, T.F.: Algorithms for finding global minimizers of image segmentation and denoising models. SIAM Jour. Appl. Math. 66(5), 1632–1648 (2006)
Chambolle, A.: An algorithm for total variation minimization and applications. Jour. Math. Imag. Vis. 20(1-2), 89–97 (2004)
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Bao, Z., Liu, Y., Peng, Y., Zhang, G. (2010). Variational Color Image Segmentation via Chromaticity-Brightness Decomposition. In: Boll, S., Tian, Q., Zhang, L., Zhang, Z., Chen, YP.P. (eds) Advances in Multimedia Modeling. MMM 2010. Lecture Notes in Computer Science, vol 5916. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11301-7_31
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DOI: https://doi.org/10.1007/978-3-642-11301-7_31
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