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Removing Reflection From a Single Image With Ghosting Effect

机译:用重影效应从单个图像中移除反射

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摘要

Removing the undesired reflections of images taken through glass is an important problem in digital photography and many other vision applications. The so-called ghosting effect, i.e., the pattern repetitiveness in reflection, is an effective cue used by existing techniques to remove reflection from images. Existing methods take a two-stage approach that first estimates the parameters of ghosting effect and then models reflection removal as a two-layer separation problem: reflection layer and latent image layer. This paper aims at addressing one main challenge in such an approach, i.e., how to distinguish the repetitive patterns on the later image layer and the ghosting patterns on the reflection layer. Based on the observation that the number of repeats of natural image patterns is often different from that of ghosting patterns, we propose a wavelet transform based regularization method. Together with a novel weighting scheme, the proposed method is capable of accurately separating two layers, and experimental results justified its advantages over the existing ones on both synthetic and real data set.
机译:去除通过玻璃拍摄的图像的不期望的反射是数字摄影和许多其他视觉应用中的重要问题。所谓的重影效应,即反射中的模式重复性,是现有技术用于去除图像反射的现有技术的有效提示。现有方法采用两阶段方法,首先估计重影效应的参数,然后模拟反射移除作为双层分离问题:反射层和潜像层。本文旨在以这种方法解决一个主要挑战,即如何区分后来图像层上的重复模式和反射层上的重影模式。基于观察到,自然图像图案的重复数量通常与重影模式的数量不同,我们提出了一种基于小波变换的正则化方法。与一种新颖的加权方案一起,该方法能够精确地分离两层,实验结果使其在合成和实际数据集上的现有数据上的优势。

著录项

  • 来源
    《Computational Imaging, IEEE Transactions on》 |2020年第2020期|34-45|共12页
  • 作者单位

    School of Computer Science and Engineering South China University of Technology Guangzhou China;

    School of Computer Science and Engineering South China University of Technology Guangzhou China;

    School of Computer Science and Engineering South China University of Technology Guangzhou China;

    School of Computer Science and Engineering South China University of Technology Guangzhou China;

    Department of Mathematics at National University of Singapore Singapore;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Glass; Windows; Microsoft Windows; Brightness; Cameras; Kernel;

    机译:玻璃;窗户;微软Windows;亮度;相机;内核;

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