IEEE Trans Image Process. 2018 Oct;27(10):4873-4888. doi: 10.1109/TIP.2018.2849880.
The images taken through glass often capture a target transmitted scene as well as undesired reflected scenes. In this paper, we propose a novel reflection removal algorithm using multiple glass images taken from slightly different camera positions. We first find co-saliency maps for input multiple glass images based on the center prior assumption, and then align multiple images reliably with respect to the transmitted scene by selecting feature points with high co-saliency values. The gradients of the transmission images are consistent while the gradients of the reflection images are varying across the aligned multiple glass images. Based on this observation, we compute gradient reliability such that the pixels belonging to consistent salient edges of the transmission image are assigned high reliability values. We restore the gradients of the transmission images and suppress the gradients of the reflection images by formulating a low-rank matrix completion problem in gradient domain. Finally, we reconstruct desired transmission images from the restored transmission gradients. Experimental results show that the proposed algorithm removes the reflection artifacts from glass images faithfully and outperforms the existing methods on challenging glass images with diverse characteristics.
通过玻璃拍摄的图像通常会捕获目标传输场景以及不需要的反射场景。在本文中，我们提出了一种新的反射去除算法，该算法使用从略微不同的相机位置拍摄的多个玻璃图像。我们首先基于中心先验假设为输入的多个玻璃图像找到共显著图，然后通过选择具有高共显著值的特征点可靠地对齐多个图像相对于传输场景。传输图像的梯度是一致的，而反射图像的梯度在对齐的多个玻璃图像中是变化的。基于这一观察，我们计算梯度可靠性，以便将属于传输图像的一致显著边缘的像素分配高可靠性值。我们通过在梯度域中构建低秩矩阵补全问题来恢复传输图像的梯度并抑制反射图像的梯度。最后，我们从恢复的传输梯度中重建所需的传输图像。实验结果表明，该算法能够忠实地从玻璃图像中去除反射伪影，并且在具有不同特征的具有挑战性的玻璃图像上优于现有方法。
