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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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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