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.