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Removing Shadows From Images using Retinex

机译:使用Retinex从图像中去除阴影

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摘要

The Retinex Theory first introduced by Edwin Land forty years ago has been widely used for a range of applications. It was first introduced as a model of our own visual processing but has since been used to perform a range of image processing tasks including illuminant correction, dynamic range compression, and gamut mapping. In this paper we show how the theory can be extended to perform yet another image processing task: that of removing shadows from images. Our method is founded on a simple modification to the original, path based retinex computation such that we incorporate information about the location of shadow edges in an image. We demonstrate that when the location of shadow edges is known the algorithm is able to remove shadows effectively. We also set forth a method for the automatic location of shadow edges which makes use of a 1-d illumination invariant image proposed in previous work. In this case the location of shadow edges is imperfect but we show that even so, the algorithm does a good job of removing the shadows.
机译:埃德温·兰德(Edwin Land)四十年前首次提出的Retinex理论已被广泛用于各种应用中。它最初是作为我们自己的视觉处理模型引入的,但此后已被用于执行一系列图像处理任务,包括光源校正,动态范围压缩和色域映射。在本文中,我们展示了如何扩展该理论以执行另一个图像处理任务:从图像中去除阴影。我们的方法基于对原始的基于路径的retinex计算的简单修改,因此我们将有关图像中阴影边缘位置的信息合并在一起。我们证明了当阴影边缘的位置已知时,该算法能够有效地去除阴影。我们还提出了一种自动确定阴影边缘的方法,该方法利用了先前工作中提出的一维照明不变图像。在这种情况下,阴影边缘的位置并不完美,但是我们证明即使如此,该算法也可以很好地去除阴影。

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