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Image colorization by fusion of color transfers based on DFT and variance features

机译:通过基于DFT和方差特征的颜色转移融合实现图像着色

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Color transfer methods usually suffer from spatial color coherency problem. In order to address this problem, this paper develops a fused color transfer method for image colorization. Our idea is to design a local student's t-test to screen the incoherent colors in the preliminary colorization results obtained by a simple color transfer method with DFT and variance features. Furthermore, we propose a variational fusion model to inpaint these incoherent colors and fuse the other useful colors together. We also present an efficient algorithm for solving the fusion model numerically, and show the convergence of the algorithm. Finally, experimental results are reported to demonstrate the effectiveness of the proposed method, and its performance is competitive with those of the other testing methods. (C) 2018 Elsevier Ltd. All rights reserved.
机译:颜色转移方法通常遭受空间颜色一致性问题。为了解决这个问题,本文开发了一种用于图像着色的融合颜色转移方法。我们的想法是设计一个本地学生的t检验,以筛选通过具有DFT和方差特征的简单颜色转移方法获得的初步着色结果中不相干的颜色。此外,我们提出了一种变分融合模型来修补这些不连贯的颜色,并将其他有用的颜色融合在一起。我们还提出了一种数值求解融合模型的有效算法,并展示了该算法的收敛性。最后,据报道实验结果证明了该方法的有效性,其性能与其他测试方法相比具有竞争力。 (C)2018 Elsevier Ltd.保留所有权利。

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