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Region-Based Color Transfer for Complex Content Images Using Intrinsic Component

机译:使用内在分量的复杂内容图像的基于区域的颜色转移

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This paper proposes an automatic color transfer method for complex content images. When given one or more high-quality reference images, our goal is to determine a set of best reference colors for transferring their color characteristics into the target image. Although several automatic color transfer methods have been proposed, there usually exists visible and unnatural artifact when processing images with complex content and lighting variation. In this paper, we represent each image in region level and propose to incorporate region attribute, region connectivity and intrinsic reflectivity to characterize the local organization within an image. We then determine the best-matched reference region for each target region using the proposed graph-theoretic region correspondence estimation. After determining the set of reference regions, we next conduct color transfer between the best-matched region pairs in a de-correlated color space. In order to reduce artifact across complex regions, we further propose a weighted color transfer in terms of intrinsic component. Both subjective and objective evaluation of our experiments demonstrates that the proposed method outperforms existing methods.
机译:本文提出了一种用于复杂内容图像的自动颜色转移方法。当给定一个或多个高质量参考图像时,我们的目标是确定一组最佳参考颜色,以将其颜色特征传递到目标图像中。尽管已经提出了几种自动颜色转移方法,但是当处理具有复杂内容和光照变化的图像时,通常会存在可见和不自然的伪像。在本文中,我们在区域级别上代表每幅图像,并提出合并区域属性,区域连通性和固有反射率来表征图像中的局部组织。然后,我们使用提议的图论区域对应估计来确定每个目标区域的最佳匹配参考区域。确定参考区域集后,我们接下来在去相关的颜色空间中的最匹配区域对之间进行颜色转移。为了减少复杂区域中的伪影,我们进一步提出了一种基于固有成分的加权颜色转移。我们的实验的主观和客观评估都表明,所提出的方法优于现有方法。

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