BUILDING COLOR-MANAGEMENT MODULES USING LINEAR OPTIMIZATION I - DESK-TOP COLOR SYSTEM

Two kinds of models were derived that predicted spectral reflectance f actor of colors formed using an ink-jet printer. One was the spectral Murray-Davies-Yule-Nielsen model in which n-value was assumed to vary as a function of wavelength. The other was based on the Omatsu model i n which the path length of light scattering was assumed to vary as a f unction of wavelength. Model parameters were optimized using a test ta rget of 57 samples consisting of cyan, magenta, yellow, red, green, bl ue, and black colors varying between white and the maximum ink amount. Average accuracy of an independent data set sampling the printer's co lor gamut was 4.2 and 3.9 Delta E-ab, for the Murray-Davies-Yule-Niel sen and the Omatsu models, respectively. The difference in performance was not significant. The Yule-Nielsen model was selected to build dev ice profiles because of its simplicity in comparison to the Omatsu mod el. A desktop scanner was colorimetrically characterized using a multi ple-linear-regression model to build a concatenated device profile in which digital counts of a scanned photographic reflection print were t he input and those of the printer were the output. Because the printer model was analytically noninvertable, the Newton-Raphson and the Simp lex iterative methods were evaluated as candidate optimization methods to build 33 x 33 x 33 color look-up tables. These tables were evaluat ed by comparing a photographic reflection IT8.7/2 target with its prin ted reproduction. The Simplex method yielded superior results, particu larly for colors near the edge or outside of the printer's color gamut . The average Delta E-ab, error from a profile based on the Simplex m ethod was 5.9 including colors outside of the printer's color gamut.