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Recovering Intrinsic Images from a Single Image

机译:从单个图像中恢复内部图像

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We present an algorithm that uses multiple cues to recover shading and reflectance intrinsic images from a single image. Using both color information and a classifier trained to recognize gray-scale patterns, each image derivative is classified as being caused by shading or a change in the surface's reflectance. Generalized Belief Propagation is then used to propagate information from areas where the correct classification is clear to areas where it is ambiguous. We also show results on real images.
机译:我们提出了一种使用多个提示来恢复从单个图像恢复阴影和反射率的算法。使用培训的颜色信息和培训以识别灰度模式的分类器,每个图像导数被归类为由遮蔽或表面的反射率的变化引起的。然后,使用广义信念传播从正确分类对其模糊的区域传播信息。我们还显示实际图像的结果。

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