Abstract
Converting color images into grayscale ones suffer from information loss. In the meantime, it is one fundamental tool indispensable for single channel image processing, digital printing, and monotone e-ink display. In this paper, we propose an optimization framework aiming at maximally preserving color contrast. Our main contribution is threefold. First, we employ a bimodal objective function to alleviate the restrictive order constraint for color mapping. Second, we develop an efficient solver that allows for automatic selection of suitable grayscales based on global contrast constraints. Third, we advocate a perceptual-based metric to measure contrast loss, as well as content preservation, in the produced grayscale images. It is among the first attempts in this field to quantitatively evaluate decolorization results.
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Notes
It is suggested in Chen and Wang (2004) that \(\tau <6\) makes structures imperceivable to human visual system.
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Acknowledgments
The authors would like to thank the editor and all the anonymous reviewers for their time and effort. This work is supported by a grant from the Research Grants Council of the Hong Kong SAR (Project No. 413110) and by NSF of China (key Project No. 61133009).
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Communicated by Dr. Srinivas Narasimhan, Dr. Frédo Durand and Dr. Wolfgang Heidrich.
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Lu, C., Xu, L. & Jia, J. Contrast Preserving Decolorization with Perception-Based Quality Metrics. Int J Comput Vis 110, 222–239 (2014). https://doi.org/10.1007/s11263-014-0732-6
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DOI: https://doi.org/10.1007/s11263-014-0732-6