Representation of Color Space Transformations for Effective Calibration and Control

We propose the minvar algorithm for computing continuous, continuously invertible, piecewise linear (PL) approximations of color space transformations that can serve as functional replacements wherever look-up tables are presently used. After motivating the importance of invertible approximants in color space management applications, we review the parameterization and computational implementation of PL functions as representing one useful instance of this notion. Finally, we describe the present version of the minvar algorithm and compare the approximations it yields with standard industrial practice — interpolation of look-up table data

Modeling and Control of Color Xerographic Processes

The University of Michigan and Xerox\u27s Wilson Research Center have been collaborating on problems in color management systems since 1996, supported in part by an NSF GOALI grant. The paper is divided into three sections. The first discusses the basics of xerography and areas where systems methodology can have a potential impact. The second section describes the authors\u27 approach to the approximation of color space transformations using piecewise linear approximants and the graph intersection algorithm, with a brief review of some of the analytical and numerical results. The last section expounds on some of the benefits and difficulties of industry-university-government collaboration

Toward a Control Oriented Model of Xerographic Marking Engines

This paper presents some preliminary results from a research collaboration concerning the modeling and control of color xerography. In this first communication of our work, we describe our efforts to develop a model for a monochrome marking engine. We adopt the technique of principal component analysis for choice of output coordinates and demonstrate preliminary experimental evidence suggesting that this procedure yields accuracy in data reconstruction superior to present industry practice. Preliminary analysis of the experimental evidence suggests that the process has a nonlinear component that we seek to model using a mixture of physical and empirical insight