期刊
VISUAL COMPUTER
卷 35, 期 2, 页码 205-221出版社
SPRINGER
DOI: 10.1007/s00371-017-1464-8
关键词
Color-to-gray conversion; Weighted projection; Linear parametric model; Projected gradient descent; Nonnegative constraint; Discrete searching
资金
- National Natural Science Foundation of China [61661031, 61362001, 61365013, 61503176]
- international scientific and technological cooperation projects of Jiangxi Province [20141BDH80001]
- Young scientists training plan of Jiangxi province [20142BCB23001, 20162BCB23019]
This paper presents a novel semi-reference inspired color-to-gray conversion model for faithfully preserving the contrast details of the color image, essentially differs from most of the no-reference and reference approaches. In the proposed model, on the basic assumption that a good gray conversion should make the conveyed gradient values (i.e., contrast) to be maximal, we present a projection maximum function to model the decolorization procedure. We further incorporate weights of the original gradients into the maximum function. The Gaussian weighted factor consisting of the gradients of each channel of the input color image is employed to better reflect the degree of preserving feature discriminability and color ordering in color-to-gray conversion. The projected gradient descent and discrete searching techniques are developed to solve the proposed model with and without nonnegative constraint, respectively. Extensive experimental evaluations on two existing datasets, containing abundant colors and patterns, show that the proposed method outperforms the state-of-the-art methods quantitatively and qualitatively.
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