用于像素级光源估计的因子图

Lawrence Mutimbu, A. Robles-Kelly
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引用次数: 2

摘要

本文提出了一种多光源照明场景的逐像素光源颜色恢复方法。在这里,我们从图像的形成过程出发,将手头的光源恢复任务置于证据组合设置中。为此,我们利用输入图像的尺度空间和一组光源原型构建了一个因子图。这些原型的计算是数据驱动的,因此,我们的方法不需要库或用户输入。因子图的使用允许利用最大后验(MAP)推理过程恢复不同尺度上的光源估计。此外,我们通过使用Delaunay三角剖分构造因子图来精确地计算这里使用的概率边际。我们说明了我们的方法在两个广泛可用的数据集上的像素照明颜色恢复的效用,并与许多替代方案进行了比较。我们还展示了真实世界图像的样本色彩校正结果。
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Factor graphs for pixelwise illuminant estimation
This paper presents a method to recover the pixel-wise illuminant colour for scenes lit by multiple lights. Here, we start from the image formation process and pose the illuminant recovery task in hand into an evidence combining setting. To do this, we construct a factor graph making use of the scale space of the input image and a set of illuminant prototypes. The computation of these prototypes is data driven and, hence, our method is devoid of libraries or user input. The use of a factor graph allows for the illuminant estimates at different scales to be recovered making use of a maximum a posteriori (MAP) inference process. Moreover, we render the computation of the probability marginals used here as exact by constructing our factor graph making use of a Delaunay triangulation. We illustrate the utility of our method for pixelwise illuminant colour recovery on two widely available datasets and compare against a number of alternatives. We also show sample colour correction results on real-world images.
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