Volume 16, Issue 4
Color-To-Gray Conversion with Perceptual Preservation and Dark Channel Prior

Jun Liu, Faming Fang & Ning Du

DOI:

Int. J. Numer. Anal. Mod., 16 (2019), pp. 668-679.

Published online: 2019-02

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  • Abstract

This paper aims to present a decolorization strategy based on perceptual consistency and dark channel prior. The proposed model consists of effective fidelity terms and a prior term. We use the $\mathcal{l}$0-norm to control the sparsity of the dark channel prior. To solve the non-convex minimization problem, we employ the split and penalty technique to simplify the minimization problem and then solve it by the carefully designed iteration scheme. Besides, we show the convergence of the algorithm using Kurdyka- Lojasiewicz property. The numerical evaluation in comparison with other state-of-the-art methods demonstrates the effectiveness of the proposed method.

  • Keywords

Color-to-gray, perceptual consistency, dark channel, Kurdyka- Lojasiewicz property, non-convex.

  • AMS Subject Headings

65K10, 68U10, 68W40, 90C26

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address

liuj292@nenu.edu.cn (Jun Liu)

fmfang@cs.ecnu.edu.cn (Faming Fang)

dun933@nenu.edu.cn (Ning Du)

  • BibTex
  • RIS
  • TXT
@Article{IJNAM-16-668, author = {Liu , Jun and Fang , Faming and Du , Ning }, title = {Color-To-Gray Conversion with Perceptual Preservation and Dark Channel Prior}, journal = {International Journal of Numerical Analysis and Modeling}, year = {2019}, volume = {16}, number = {4}, pages = {668--679}, abstract = {

This paper aims to present a decolorization strategy based on perceptual consistency and dark channel prior. The proposed model consists of effective fidelity terms and a prior term. We use the $\mathcal{l}$0-norm to control the sparsity of the dark channel prior. To solve the non-convex minimization problem, we employ the split and penalty technique to simplify the minimization problem and then solve it by the carefully designed iteration scheme. Besides, we show the convergence of the algorithm using Kurdyka- Lojasiewicz property. The numerical evaluation in comparison with other state-of-the-art methods demonstrates the effectiveness of the proposed method.

}, issn = {2617-8710}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/ijnam/13020.html} }
TY - JOUR T1 - Color-To-Gray Conversion with Perceptual Preservation and Dark Channel Prior AU - Liu , Jun AU - Fang , Faming AU - Du , Ning JO - International Journal of Numerical Analysis and Modeling VL - 4 SP - 668 EP - 679 PY - 2019 DA - 2019/02 SN - 16 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/ijnam/13020.html KW - Color-to-gray, perceptual consistency, dark channel, Kurdyka- Lojasiewicz property, non-convex. AB -

This paper aims to present a decolorization strategy based on perceptual consistency and dark channel prior. The proposed model consists of effective fidelity terms and a prior term. We use the $\mathcal{l}$0-norm to control the sparsity of the dark channel prior. To solve the non-convex minimization problem, we employ the split and penalty technique to simplify the minimization problem and then solve it by the carefully designed iteration scheme. Besides, we show the convergence of the algorithm using Kurdyka- Lojasiewicz property. The numerical evaluation in comparison with other state-of-the-art methods demonstrates the effectiveness of the proposed method.

Jun Liu, Faming Fang & Ning Du. (2019). Color-To-Gray Conversion with Perceptual Preservation and Dark Channel Prior. International Journal of Numerical Analysis and Modeling. 16 (4). 668-679. doi:
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