Pseudo multivariate morphological operators based on alpha-trimmed lexicographical extrema

Abstract : The extension of mathematical morphology to color and more generally to multivariate image data is still an open problem. The definition of multivariate morphological operators requires the introduction of a complete lattice structure on the image data, hence vectorial extrema computation methods are necessary. In this paper, we propose a lexicographical approach with this end, based on the principle of a-trimming, that leads to flexible, but nevertheless pseudo-morphological operators, in the sense that there is no underlying binary ordering relation among the vectors. Moreover a possible solution to this problem is presented as well as a way of automatically computing the parameter a based on statistical measures. The results of a series of color noise reduction experiments are also included, illustrating the superior performance of the proposed approach against uncorrelated Gaussian noise, with respect to state-of-the-art vector ordering schemes.
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Communication dans un congrès
5th International Symposium on Image and Signal Processing and Analysis (ISPA), 2007, Turkey. pp.367-372, 2007, <10.1109/ISPA.2007.4383721>
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Dernière modification le : mercredi 8 septembre 2010 - 21:19:05
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Erchan Aptoula, Sébastien Lefèvre. Pseudo multivariate morphological operators based on alpha-trimmed lexicographical extrema. 5th International Symposium on Image and Signal Processing and Analysis (ISPA), 2007, Turkey. pp.367-372, 2007, <10.1109/ISPA.2007.4383721>. <hal-00516074>

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