KEYWORDS: Scanners, Printing, RGB color model, CMYK color model, 3D acquisition, Calibration, Diagnostics, 3D printing, 3D imaging standards, Halftones
We propose a novel scanner characterization approach for applications requiring color measurement of hardcopy output in printer calibration, characterization, and diagnostic applications. It is assumed that a typical printed medium comprises the three basic colorants C, M, Y. The proposed method is particularly advantageous when additional colorants are used in the print (e.g. black (K)). A family of scanner characterization targets is constructed, each varying in C, M, Y and at a fixed level of K. A corresponding family of 3-D scanner characterizations is derived, one for each level of K. Each characterization maps scanner RGB to a colorimetric representation such as CIELAB, using standard characterization techniques. These are then combined into a single 4-D characterization mapping RGBK to CIELAB. A refinement of the technique improves performance significantly by using a function of the scanned values for K (e.g. the scanner's green channel response to printed K) instead of the digital K value directly. This makes this new approach more robust with respect to variations in printed K over time. Secondly it enables, with a single scanner characterization, accurate color measurement of prints from different printers within the same family. Results show that the 4-D characterization technique can significantly outperform standard 3-D approaches especially in cases where the image being scanned is a
patch target made up of unconstrained CMYK combinations. Thus the algorithm finds particular use in printer characterization and diagnostic applications. The method readily generalizes to printed media containing other (e.g "hi-fi") colorants, and also to other image capture devices such as digital cameras.
We have developed a color reproduction software for a digital still camera. The image taken by the camera was colorimetrically reproduced on the monitor after characterizing the camera and the monitor, and color matching between two devices. The reproduction was performed at three levels; level processing, gamma correction, and color transformation. The image contrast was increased after the level processing adjusting the level of dark and bright portions of the image. The relationship between the level processed digital values and the measured luminance values of test gray samples was calculated, and the gamma of the camera was obtained. The method for getting the unknown monitor gamma was proposed. As a result, the level processed values were adjusted by the look-up table created by the camera and the monitor gamma correction. For a color transformation matrix for the camera, 3 by 3 or 3 by 4 matrix was used, which was calculated by the regression between the gamma corrected values and the measured tristimulus values of each test color samples the various reproduced images were displayed on the dialogue box implemented in our software, which were generated according to four illuminations for the camera and three color temperatures for the monitor. An user can easily choose he best reproduced image comparing each others.
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