Automatic Exposure Compensation for Multi-Exposure Image Fusion
Automatic Exposure Compensation for Multi-Exposure Image Fusion
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DOI：
10.1109/icip.2018.8451401
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发表时间：
2018-05
期刊：
影响因子：
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通讯作者：
Yuma Kinoshita;Sayaka Shiota;H. Kiya
中科院分区：
文献类型：
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作者：
Yuma Kinoshita;Sayaka Shiota;H. Kiya
针对多曝光图像融合问题，提出了一种基于自动曝光补偿的亮度调整方法.多曝光图像融合是指利用不同曝光的照片，产生无饱和区域的图像。在传统的工作中，已经指出，可以通过调整这些多重曝光图像的亮度来提高它们的质量。但是，如何确定调整的程度，从来没有讨论过。因此，本文提出了一种方法来自动确定的程度的基础上的亮度分布的输入多曝光图像。此外，新的权重，称为“简单的权重”，图像融合也被认为是建议的亮度调整方法。实验结果表明，该方法调整后的多次曝光图像在曝光度方面优于输入的多次曝光图像。它也被证实，建议简单的权重提供了最高的分数的统计自然度和离散熵在所有的融合方法。
This paper proposes a novel luminance adjustment method based on automatic exposure compensation for multi -exposure image fusion. Multi-exposure image fusion is a method to produce images without saturation regions, by using photos with different exposures. In conventional works, it has been pointed out that the quality of those multi-exposure images can be improved by adjusting the luminance of them. However, how to determine the degree of adjustment has never been discussed. This paper therefore proposes a way to automatically determines the degree on the basis of the luminance distribution of input multi -exposure images. Moreover, new weights, called “simple weights”, for image fusion are also considered for the proposed luminance adjustment method. Experimental results show that the multi -exposure images adjusted by the proposed method have better quality than the input multi-exposure ones in terms of the well-exposedness. It is also confirmed that the proposed simple weights provide the highest score of statistical naturalness and discrete entropy in all fusion methods.