Cartoon and Texture Decomposition-Based Color Transfer for Fabric Images
Cartoon and Texture Decomposition-Based Color Transfer for Fabric Images
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基于卡通和纹理分解的织物图像颜色传输
DOI：
10.1109/tmm.2016.2608000
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发表时间：
2017
影响因子：
7.3
通讯作者：
Islam Md. Robiul
中科院分区：
文献类型：
--
作者：
Han Yu;Xu Chen;Baciu George;Li Min;Islam Md. Robiul
织物图像的色彩设计过程可以基于给定的色彩主题来解决色彩传递问题。通常，颜色转移过程包含图像分割阶段和图像构建阶段。本文提出了一种新的织物图像颜色转移方法。与经典的颜色传递方法相比，新方法主要有以下三个创新点。首先，新方法在其图像分割阶段遵循织物图像可以分解为卡通和纹理分量的假设，这意味着新的颜色转移方法在其图像分割阶段结合了图像分解过程。该创新的优点在于卡通组件比原始图像更适合用于分割织物图像。第二，新的颜色转移方法可以产生更生动的颜色转移结果，因为上述纹理成分用于描述纱线纹理细节在图像构建阶段。第三，使用全广义变分（TGV）正则化器进一步提高图像分解的性能。这里，TGV正则化器擅长于用CIELab颜色方案估计卡通分量的弱亮度变化。此外，利用增广的拉格朗日乘子法，我们推导出一个有效的算法来搜索所提出的颜色传递问题的解决方案。数值结果表明，所提出的颜色转移方法可以产生更好的效果，织物图像。
A color design process for fabric images can resort to a solution of a color transfer problem based on given color themes. Usually, the color transfer process contains an image segmentation phase and an image construction phase. In this paper, a novel color transfer method for fabric images is proposed. Compared with classical color transfer methods, the new method has the following three main innovations. First, the new method, in its image segmentation phase, follows an assumption that a fabric image can be decomposed into cartoon and texture components, which means the new color transfer method, in its image segmentation, phase incorporates an image decomposition process. The advantage of the innovation is that the cartoon component is more suitable than the original image to be used to partition the fabric image. Second, the new color transfer method can generate more vivid color transfer results since the above texture component is used to describe yarn texture details in the image construction phase. Third, the total generalized variation (TGV) regularizer is used to further improve the performance of image decomposition. Here, the TGV regularizer is good at estimating the weak lightness variation of the cartoon component with the CIELab color scheme. In addition, by using the augmented Lagrange multiplier method, we derive an efficient algorithm to search for the solutions to the proposed color transfer problem. Numerical results demonstrate that the proposed color transfer method can generate better results for fabric images.
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影响因子：
2
作者：
T. Chan;S. Kang
通讯作者：
T. Chan;S. Kang
基于示例的颜色传输的损坏伪影抑制
影响因子：
7.3
作者：
Kun Zeng;Li Liu;Bo Li;Xiaonan Luo
通讯作者：
Xiaonan Luo
DOI：
10.1109/tpami.2007.1053
发表时间：
2007-05
影响因子：
23.6
作者：
Wen-Chieh Lin;Yanxi Liu
通讯作者：
Wen-Chieh Lin;Yanxi Liu
DOI：
10.1016/j.jvcir.2011.09.006
发表时间：
2012
期刊：
J. Vis. Commun. Image Represent.
影响因子：
--
作者：
Shiguang Liu;Hanqiu Sun;Xiang Zhang
通讯作者：
Shiguang Liu;Hanqiu Sun;Xiang Zhang
DOI：
10.1109/icci-cc.2012.6311173
发表时间：
2012-08
期刊：
2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing
影响因子：
--
作者：
Dejun Zheng;Yu Han;G. Baciu;Jinlian Hu
通讯作者：
Dejun Zheng;Yu Han;G. Baciu;Jinlian Hu