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29 March 1996 Refinement of printer transformations using weighted regression
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Proceedings Volume 2658, Color Imaging: Device-Independent Color, Color Hard Copy, and Graphic Arts; (1996)
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States
Printer characterization and color correction are often complex transformations, and are derived with numerous measurements or printer models. There are many sources of errors in these transforms, including inaccuracies in lookup table approximation, errors in the printer model, noise in the data, and spatial and temporal non-uniformities in the printer. A method is proposed to increase the accuracy of an existing printer transform with a relatively small number of refinement measurements. A weighted linear least-squares regression technique is used to improve the fit of the printer response to the refinement data. The hypothesis is that a locally linear transform can adequately capture the difference between the true printer transform and its approximation. In contrast to existing approaches that only refine the individual C, M, Y, K responses, the proposed method attempts to account for cross-colorant interactions by using mixed colors in the refinement set. Furthermore, the refinement data is not restricted to lying on a regular grid, and can be freely chosen based on any a priori knowledge about the printer. The approach is tested for two related transforms: the characterization transform which maps CMYK to L*a*b*; and its inverse, the color correction transform that maps L*a*b* to CMYK. Results show an improvement in transform accuracy with a relatively small number of measurements.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Raja Balasubramanian and Martin S. Maltz "Refinement of printer transformations using weighted regression", Proc. SPIE 2658, Color Imaging: Device-Independent Color, Color Hard Copy, and Graphic Arts, (29 March 1996);

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