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A Detail-Preserved and Luminance-Consistent Multi-Exposure Image Fusion Algorithm

机译:保留细节且亮度一致的多曝光图像融合算法

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When irradiance across a scene varies greatly, we can hardly get an image of the scene without over- or underexposure area, because of the constraints of cameras. Multi-exposure image fusion (MEF) is an effective method to deal with this problem by fusing multi-exposure images of a static scene. A novel MEF method is described in this paper. In the proposed algorithm, coarser-scale luminance consistency is preserved by contribution adjustment using the luminance information between blocks; detail-preserved smoothing filter can stitch blocks smoothly without losing details. Experiment results show that the proposed method performs well in preserving luminance consistency and details.
机译:当整个场景的辐照度变化很大时,由于相机的限制,我们很难在没有过度或不足的曝光区域的情况下获得场景的图像。多曝光图像融合(MEF)是通过融合静态场景的多曝光图像来解决此问题的有效方法。本文介绍了一种新颖的MEF方法。在该算法中,通过利用块之间的亮度信息进行贡献调整来保持较粗尺度的亮度一致性。保留细节的平滑过滤器可以平滑地缝合块,而不会丢失细节。实验结果表明,该方法在保持亮度一致性和细节方面表现良好。

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