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Shadow Removal Using Bilateral Filtering

机译:使用双边过滤去除阴影

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摘要

In this paper, we propose a simple but effective shadow removal method using a single input image. We first derive a 2-D intrinsic image from a single RGB camera image based solely on colors, particularly chromaticity. We next present a method to recover a 3-D intrinsic image based on bilateral filtering and the 2-D intrinsic image. The luminance contrast in regions with similar surface reflectance due to geometry and illumination variances is effectively reduced in the derived 3-D intrinsic image, while the contrast in regions with different surface reflectance is preserved. However, the intrinsic image contains incorrect luminance values. To obtain the correct luminance, we decompose the input RGB image and the intrinsic image. Each image is decomposed into a base layer and a detail layer. We obtain a shadow-free image by combining the base layer from the input RGB image and the detail layer from the intrinsic image such that the details of the intrinsic image are transferred to the input RGB image from which the correct luminance values can be obtained. Unlike previous methods, the presented technique is fully automatic and does not require shadow detection.
机译:在本文中,我们提出了一种使用单个输入图像的简单但有效的阴影去除方法。我们首先仅根据颜色(特别是色度)从单个RGB相机图像中得出2D内部图像。接下来,我们提出一种基于双边滤波和2D内部图像恢复3D内部图像的方法。由于几何形状和照明差异而在具有相似表面反射率的区域中的亮度对比度在导出的3-D本征图像中得到有效降低,而具有不同表面反射率的区域中的对比度得以保留。但是,固有图像包含不正确的亮度值。为了获得正确的亮度,我们分解了输入的RGB图像和本征图像。每个图像被分解为基础层和细节层。我们通过组合输入RGB图像的基础层和本征图像的细节层,从而将本征图像的细节转移到输入RGB图像,从而获得正确的亮度值,从而获得无阴影图像。与以前的方法不同,本文提出的技术是全自动的,不需要阴影检测。

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