Back to articles
Articles
Volume: 18 | Article ID: art00062
Image
Optimized Construction of ICC Profiles by Lattice Regression
  DOI :  10.2352/CIC.2010.18.1.art00062  Published OnlineJanuary 2010
Abstract

We focus on a recently proposed regression framework termed lattice regression, as applied to the construction of multidimensional color management look-up tables from empirical measurements. The key idea of lattice regression is that the construction of a look-up table should take into account the interpolation function used in its final implementation. Lattice regression solves for the look-up table (LUT) that minimizes the error of interpolating the empirical measurements (training samples) and regularization is added to promote smoothness and enable extrapolation. The main contribution of this paper is the proposal and analysis of using the thin-plate regularizer for lattice regression to produce smooth and accurate color transformations. Experiments with a consumer inkjet and laser printer show that the proposed regularizer obtains similar accuracy to the previously-proposed (and more complicated) combination of Laplacian and globalbias regularizers, and that both can create significantly more accurate and smoother results than a state-of-the-art locally linear approach.

Subject Areas :
Views 5
Downloads 0
 articleview.views 5
 articleview.downloads 0
  Cite this article 

Eric Garcia, Maya Gupta, "Optimized Construction of ICC Profiles by Lattice Regressionin Proc. IS&T 18th Color and Imaging Conf.,  2010,  pp 353 - 358,  https://doi.org/10.2352/CIC.2010.18.1.art00062

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2010
72010350
Color and Imaging Conference
color imaging conf
2166-9635
Society of Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151, USA