Image transformation into device-dependent color printer description using 4th-order polynomial regression and object-oriented programming development of image processing modules

Michael C. Mongeon

doi:10.1117/12.236985

29 March 1996 Image transformation into device-dependent color printer description using 4th-order polynomial regression and object-oriented programming development of image processing modules

Michael C. Mongeon

Author Affiliations +

Proceedings Volume 2658, Color Imaging: Device-Independent Color, Color Hard Copy, and Graphic Arts; (1996) https://doi.org/10.1117/12.236985
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States

Abstract

This paper investigates the development of printer device profiles used in color document printing system environments when devices with intrinsically different gamut capabilities communicate with one another in a common (CIELAB) color space. While the main thrust of this activity focuses on the output printer, namely the Xerox 5760 printer, and its rendition of some device independent image description, characterizations are provided which investigate relative areas of photographic, monitor, and printer gamuts using a visual hue leaf comparison between devices. The printer is modeled using 4th-order polynomial regression which maps the device independent CIELAB image representation into device dependent printer CMYK. This technique results in 1.89 AEEavg over the training data set. Some key properties of the proposed calibration method are as follows: (1) Linearized CMYK tone reproduction curves with respect to AEEpaper to improve the distribution of calibration data in color space. (2) Application of GCR strategy and linearization to the calibration target prior to the regression on the measured CIELAB and original CMY values. Each strategy employs a K addition/No CMY removal method which maximizes printer gamut and relies on the regression to determine the appropriate CMY removal. The following GCR strategies are explored: CMY only (0% K addition), 50% K addition, 100% K addition, and non-linear K addition. A library of image processing algorithms is included, using LabView object oriented programming, which provides a modular approach for key color processing tasks. In the user interface, an image is selected with appropriate GCR strategy, and the program operates on the image. In general, the pictorial image quality is excellent for each GCR strategy with subtle differences between GCR approaches. Quantitative analysis of Q60 color matching performance is included.

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Michael C. Mongeon "Image transformation into device-dependent color printer description using 4th-order polynomial regression and object-oriented programming development of image processing modules", Proc. SPIE 2658, Color Imaging: Device-Independent Color, Color Hard Copy, and Graphic Arts, (29 March 1996); https://doi.org/10.1117/12.236985

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