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Single Image Glare Removal Using Deep Convolutional Networks

机译:使用深度卷积网络去除单幅图像眩光

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Deep convolutional neural networks have been investigated for atmospheric particle removal and accomplished the state-of-the-art performance. Most of the previous studies however focus on removing the effects of atmospheric particles but not on glares caused by direct or reflected sunlight on images. In this paper, we propose a decompose-refine network for single image glare removal. Specifically, our network is composed of a glare detection subnetwork and a glare removal subnetwork, which are respectively in charge of glare detection and removal. Experimental results show that our network outperforms the state-of-the-art network baselines on testing dataset.
机译:已经研究了深度卷积神经网络,用于大气颗粒去除并完成最先进的性能。然而,以前的大多数研究侧重于去除大气颗粒的影响,但不是直接或反射图像上的阳光在图像上引起的眩光。在本文中,我们提出了一种用于删除单个图像眩光的分解网络。具体而言,我们的网络由眩光检测子网和眩光去除子网组成,分别为眩光检测和移除。实验结果表明,我们的网络优于测试数据集的最先进的网络基线。

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