Shadow removal is a challenging problem due to its sensitivity to lighting and material conditions. In this paper, we propose a shading-aware shadow processing algorithm, which can automatically detect and remove complex shadows from a single color image. Our framework consists of two key steps. We firstly conduct a shadow-preserving filter upon the image which will effectively remove the image texture while preserving the shadow and shading information. Shadow regions are estimated by establishing a confidence map from the filtered image incorporating depth cue. We then develop a shading-aware optimization framework to remove shadows and recover shading in these regions. The extensive experimental results show that the proposed algorithm produces visually compelling results in a series of challenging images and it can handle complex shadows in both indoor and outdoor scenes. Quantitative and qualitative comparisons with current state-of-the-art methods strongly demonstrate the efficacy of our proposed approach.

中文翻译：

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从单个图像中进行阴影感知阴影检测和去除

由于其对光照和材料条件的敏感性，阴影去除是一个具有挑战性的问题。在本文中，我们提出了一种shading-aware的阴影处理算法，它可以自动检测和去除单色图像中的复杂阴影。我们的框架由两个关键步骤组成。我们首先对图像进行阴影保留过滤，这将有效去除图像纹理，同时保留阴影和明暗信息。通过从包含深度线索的过滤图像建立置信度图来估计阴影区域。然后，我们开发了一个阴影感知优化框架来去除这些区域中的阴影并恢复阴影。广泛的实验结果表明，所提出的算法在一系列具有挑战性的图像中产生了视觉上引人注目的结果，并且可以处理室内和室外场景中的复杂阴影。与当前最先进方法的定量和定性比较有力地证明了我们提出的方法的有效性。