从单个图像的反射场景分离

Renjie Wan, Boxin Shi, Haoliang Li, Ling-yu Duan, A. Kot
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引用次数: 17

摘要

对于透过玻璃拍摄的图像,现有的方法主要是将反射分量视为噪声来恢复背景场景。然而,玻璃表面反射出的场景也包含着重要的信息,特别是对于监视或刑事侦查来说。在本文中,我们的目标不是从混合图像中去除反射成分,而是从混合图像中恢复反射场景。我们首先提出了一种策略来获取这些基础真值及其相应的输入图像。然后,我们提出了一种两阶段框架,从混合图像中获得可见反射场景。具体来说,我们用移位不变损失训练网络,该损失对输入和输出图像之间的不对齐具有鲁棒性。实验结果表明,该方法取得了较好的效果。
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Reflection Scene Separation From a Single Image
For images taken through glass, existing methods focus on the restoration of the background scene by regarding the reflection components as noise. However, the scene reflected by glass surface also contains important information to be recovered, especially for the surveillance or criminal investigations. In this paper, instead of removing reflection components from the mixture image, we aim at recovering reflection scenes from the mixture image. We first propose a strategy to obtain such ground truth and its corresponding input images. Then, we propose a two-stage framework to obtain the visible reflection scene from the mixture image. Specifically, we train the network with a shift-invariant loss which is robust to misalignment between the input and output images. The experimental results show that our proposed method achieves promising results.
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