Journal
MULTIMEDIA TOOLS AND APPLICATIONS
Volume 76, Issue 12, Pages 14055-14074Publisher
SPRINGER
DOI: 10.1007/s11042-016-3748-9
Keywords
Color-to-gray conversion; extended RGB2GRAY conversion model; gradient correlation similarity; the linear parametric model; discrete searching
Categories
Funding
- National Natural Science Foundation of China [61362001, 61503176, 61261010, 51165033]
- Natural Science Foundation of Jiangxi Province [20151BAB207008, 20151BAB207007]
- Jiangxi Advanced Projects for Post-doctoral Research Funds [2014KY02]
- international postdoctoral exchange fellowship program
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The RGB2GRAY conversion model is the classical and most popularly used tool for image decolorization. Recent researches have validated that optimally selecting the three weighting parameters in this first-order linear model has great potential to improve its conversion ability. A question is naturally raised that extending the parameter range will count for further improvement? In this paper, we present a simple yet efficient strategy to extend the parameter range for achieving such goal. In the extended model, the parameter range is extended to be [-1, 1] and the sum of three parameters is still constrained to be 1. A discrete searching solver is proposed by determining the solution with the minimum function value from the linear parametric model induced candidate images. Among the solving procedure, the newly presented vector p-norm of gradient correlation similarity measure is utilized. Extensive experiments under a variety of test images and a comprehensive evaluation against the state-of-the-art methods consistently demonstrate the potential of the proposed model and algorithm.
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