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Local albedo-insensitive single image dehazing

机译:局部反照率不敏感的单个图像去雾

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摘要

In this paper, we present a new algorithm to remove haze from a single image. The proposed algorithm extracts transmission iteratively under the assumption that large-scale chromaticity variations are due to transmission while small-scale luminance variations are due to scene albedo. A nonlinear edge-preserving filter is introduced to incrementally refine subtle transmission map while still keeping sharp transmission map distinct. The algorithm is verified by both synthetic images and real-scene photographs. The results demonstrate that our method can produce transmission maps without being affected by the local albedo variations and, furthermore, recover haze-free images. On top of haze removal, several applications of the transmission map including refocusing and relighting are also implemented.
机译:在本文中,我们提出了一种从单个图像中去除雾度的新算法。在大规模色度变化是由于传输而小规模亮度变化是由于场景反照率的假设下,该算法迭代提取了透射率。引入了一个非线性边缘保留滤波器,以逐步细化透射图,同时仍保持清晰的透射图与众不同。该算法已通过合成图像和真实场景照片验证。结果表明,我们的方法可以生成透射图,而不受局部反照率变化的影响,而且还可以恢复无雾图像。除去除雾霾外,还实现了透射图的多种应用,包括重新聚焦和重新照明。

著录项

  • 来源
    《The Visual Computer》 |2010年第8期|761-768|共8页
  • 作者单位

    School of Computer Science and Technology, Tianjin University,Tianjin, China;

    School of Computer Science and Technology, Tianjin University,Tianjin, China;

    School of Computer Science and Technology, Tianjin University,Tianjin, China;

    School of Computer Science and Technology, Tianjin University,Tianjin, China;

    School of Computer Science and Technology, Tianjin University,Tianjin, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    image dehazing; bilateral filter; visibility restoration; contrast enhancement;

    机译:图像去雾;双边过滤器能见度恢复;对比增强;

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