It is the most crucial problem to remove ghost in the multi-exposure image fusion of dynamic scene. The traditional fusion methods have good effects to remove weak ghosts. However, they cannot effectively remove strong ghosts. This paper proposes a new strong ghost removal method in multi-exposure image fusion using hole-filling with exposure congruency. First, analyzing the characteristics of strong ghosts, a detection scheme for strong ghost regions is designed by combining histogram matching and exposure difference detection. Subsequently, to effectively extract image local features, a multi-scale fusion network for non-strong ghost regions is designed to obtain a pre-fused image. Further, based on the distribution characteristics of strong ghosts, a hole-filling model with exposure congruency is designed to remove the strong ghosts. Experimental results show that compared with the state-of-the-art methods, the proposed method can obtain better performance in both of subjective and objective evaluation, particularly in terms of effectively removing strong ghosts.

在动态场景的多曝光图像融合中，去除重影是最关键的问题。传统的融合方法去除弱鬼影效果良好。但是，它们不能有效地消除强鬼。本文提出了一种新的强重影去除方法，该方法在具有曝光一致性的空洞填充中进行多重曝光图像融合。首先，分析强重影的特征，结合直方图匹配和曝光差异检测，设计了强重影区域的检测方案。随后，为了有效地提取图像局部特征，设计了用于非强幻影区域的多尺度融合网络以获得预融合图像。此外，基于强重影的分布特征，设计了具有曝光一致性的空穴填充模型以去除强重影。