Motion-free exposure fusion based on inter-consistency and intra-consistency
Motion-free exposure fusion based on inter-consistency and intra-consistency
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DOI：
10.1016/j.ins.2016.10.020
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发表时间：
2017-01
期刊：
影响因子：
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通讯作者：
Wei Zhang;Shengnan Hu;Kang Liu;Jian Yao
中科院分区：
文献类型：
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作者：
Wei Zhang;Shengnan Hu;Kang Liu;Jian Yao
曝光融合经常遭受重影伪影，这是由动态场景被捕获时对象的移动引起的。在本文中，两种类型的一致性概念被引入，用于执行运动检测和重影去除的参考图像的指导。具体地，通过使用不同的曝光设置来削弱表示不同曝光之间的像素强度的相似性的相互一致性。采用直方图匹配的方法恢复图像的一致性。在此之后，像素差异主要是由对象移动引起的内容变化的结果，因此可以很容易地检测到运动。为了进一步抑制融合中离群点的权重，在超像素级进行运动检测，以确保具有相似强度和结构的像素共享相似的融合权重。这被称为内部一致性。在多种动态场景中的实验表明，该算法能更有效地确定运动，并能产生无重影的高质量融合结果。
Exposure fusion often suffers from ghost artifacts, which are caused by the movement of objects when a dynamic scene is captured. In this paper, two types of consistency concepts are introduced for enforcing the guidance of a reference image for motion detection and ghost removal. Specifically, the inter-consistency, which represents the similarities of pixel intensities among different exposures, is weakened by the use of different exposure settings. Histogram matching is employed to recover the inter-consistency. Following this, pixel differences are mostly the result of changes in content caused by object movements, so motion can easily be detected. To further restrain the weights of outliers in fusion, motion detection is performed at a super-pixel level, to ensure that pixels with similar intensities and structures share similar fusion weights. This is referred to as intra-consistency. Experiments in various dynamic scenes demonstrate that the proposed algorithm can determine the motion more effectively than existing methods, and produce high quality fusion results that are free of ghost artifacts.