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Proceedings Paper

Vision-based strategy to improve the color misregistration of image capturing devices
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Paper Abstract

Color misregistration is one of the common artifacts for 3-CCD desktop scanners. The misregistration of red, green and blue image layers causes both color fringing and blur in the scanned images. These effects are quantified by linear system theory analysis. Knowing the bandwidth and peak sensitivity asymmetries in the opponent color representation of the visual system, we developed a method to reduce the color misregistration artifact by attempting to capture signals in an approximate opponent color space. A new sensor arrangement facilitates this goal, in which the luminance and chrominance signals are captured independently. The luminance signal (Y) is captured at the full resolution using one row of the 3-row CCD linear arrays. The first chrominance signal is captured on another row with an interleaved half resolution red (R) and half resolution luminance sensor elements, and the second chrominance signal is similarly captured on a third row using blue (B) and luminance (Y). Since each luminance and chrominance signal is isolated on a single row, and since there is no registration error within a row, color misregistration is theoretically prevented in luminance as well as in the chrominance signals. Simulation shows that the new method does eliminate the blur and reduces the visibility of color fringing. Since residual luminance and chrominance misregistration may occur, a psychophysical experiment was conducted to judge the improvement in the scanned image quality. The experiment shows that this new capture scheme can significantly reduce the perception of misregistration artifacts.

Paper Details

Date Published: 2 June 2000
PDF: 9 pages
Proc. SPIE 3959, Human Vision and Electronic Imaging V, (2 June 2000); doi: 10.1117/12.387170
Show Author Affiliations
Xiaofan Feng, Sharp Labs. of America, Inc. (United States)
Scott J. Daly, Sharp Labs. of America, Inc. (United States)


Published in SPIE Proceedings Vol. 3959:
Human Vision and Electronic Imaging V
Bernice E. Rogowitz; Thrasyvoulos N. Pappas, Editor(s)

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