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of eight sets of error back-propagation neural networks. The results can be applied to computer-aided arts design among other things. The title of their article is âMedia-Dependent Color Appearance Modeling Based on Artiï¬cial Neural Networks.â The second article is speciï¬c to printing. In recent years various spectral models have been developed to estimate the behavior of color printers. Probably the most used and discussed model is the Yule-Nielsen modiï¬cation of the Neugebauer model. In this article, Philipp Urban and RolfRanier Grigat introduce a simple new method for âSpectralBased Color Separation Using Linear Regression Iteration.â In this model a sequence of colorant combinations is constructed that converges to the combination that approximates the desired color. The end test to conï¬rm the result is the smallest root- mean-square error. This model is particularly useful to those users who do not want to use look-up tables. In our Communications and Comments section we have a note from Manuel Melgosa. He is contributing an âImprovement of CMC upon CIEDE2000 for a New Experimental Dataset.â Last year Magine, Jakes, and Noel published âA preliminary comparison of CIE color differences to textile color acceptability using average observers,â in this journal [Vol 30: 288 â294].
Color Research & Application – Wiley
Published: Jun 1, 2006
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