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Abstract: . We merge techniques developed in the Beltrami framework to deal with multi-channel, i.e. color images, and the Mumford-Shah functional for segmentation. The result is a color image enhancement and segmentation algorithm. The generalization of the Mumford-Shah idea includes a higher dimension and codimension and a novel smoothing measure for the color components and for the segmenting function which is introduced via the \Gamma -convergence approach. We use the \Gamma -convergence... (Update)
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BibTeX entry: (Update)
Kimmel, R. and N. Sochen: 1999, `Geometric-Variational Approach for Color Image Enhancement and Segmentation'. In: M. Nielsen, P. Johansen, O. F. Olsen, and J. Weickert (eds.): Scale-space theories in computer vision, Vol. 1682 of Lecture Notes in Comp. Sci. pp. 294--305. http://citeseer.ist.psu.edu/kimmel99geometricvariational.html More
@inproceedings{ kimmel99geometricvariational,
author = "Ron Kimmel and Nir A. Sochen",
title = "Geometric-Variational Approach for Color Image Enhancement and Segmentation",
booktitle = "Scale-Space Theories in Computer Vision",
pages = "294-305",
year = "1999",
url = "citeseer.ist.psu.edu/kimmel99geometricvariational.html" }
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