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Two Illuminant Estimation and User Correction Preference

机译:两种光源估计和用户校正首选项

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This paper examines the problem of white-balance correction when a scene contains two illuminations. This is a two step process: 1) estimate the two illuminants, and 2) correct the image. Existing methods attempt to estimate a spatially varying illumination map, however, results are error prone and the resulting illumination maps are too lowresolution to be used for proper spatially varying whitebalance correction. In addition, the spatially varying nature of these methods make them computationally intensive. We show that this problem can be effectively addressed by not attempting to obtain a spatially varying illumination map, but instead by performing illumination estimation on large sub-regions of the image. Our approach is able to detect when distinct illuminations are present in the image and accurately measure these illuminants. Since our proposed strategy is not suitable for spatially varying image correction, a user study is performed to see if there is a preference for how the image should be corrected when two illuminants are present, but only a global correction can be applied. The user study shows that when the illuminations are distinct, there is a preference for the outdoor illumination to be corrected resulting in warmer final result. We use these collective findings to demonstrate an effective two illuminant estimation scheme that produces corrected images that users prefer.
机译:本文研究了场景包含两个照明时的白平衡校正问题。这是一个两步过程:1)估计两个光源,以及2)校正图像。现有方法试图估计空间变化的照明图,但是,结果容易出错,并且所得到的照明图的分辨率太低,无法用于适当的空间变化的白平衡校正。另外,这些方法的空间变化性质使它们在计算上很密集。我们表明,通过不尝试获取空间变化的照明图,而是通过对图像的较大子区域执行照明估计,可以有效解决此问题。我们的方法能够检测图像中何时存在不同的照明,并准确地测量这些照明器。由于我们提出的策略不适用于空间变化的图像校正,因此需要进行用户研究,以查看是否存在两个光源存在时如何校正图像的偏好,但是只能应用全局校正。用户研究表明,当照明不同时,更倾向于对室外照明进行校正,以得到更温暖的最终结果。我们使用这些集体的发现来证明有效的两种光源估计方案,该方案可以产生用户喜欢的校正图像。

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