Naturalness Preserved Image Enhancement Using a priori Multi-Layer Lightness Statistics.
Naturalness Preserved Image Enhancement Using a priori Multi-Layer Lightness Statistics.
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DOI：
10.1109/tip.2017.2771449
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发表时间：
2018-03
期刊：
影响因子：
--
通讯作者：
Gang Luo
中科院分区：
文献类型：
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作者：
Shuhang Wang;Gang Luo
非均匀照明图像的增强通常遭受过度增强并且产生不自然的结果。提出了一种基于高质量图像的多层亮度统计信息的非均匀光照图像自然度保持增强方法。我们的工作有三个重要的贡献：设计一种新的多层图像增强模型;推导出高质量户外图像的多层亮度统计，并将其纳入多层增强模型;以及显示增强图像的整体质量评级与对比度增强和自然度保持的组合一致。两个独立的人类观察者评价研究进行了自然保护和整体图像质量。实验结果表明，该方法优于四种比较先进的增强方法。
Enhancement of non-uniformly illuminated images often suffers from over-enhancement and produces unnatural results. This paper presents a naturalness preserved enhancement method for non-uniformly illuminated images, using a priori multi-layer lightness statistics acquired from high-quality images. Our work makes three important contributions: designing a novel multi-layer image enhancement model; deriving the multi-layer lightness statistics of high-quality outdoor images, which are incorporated into the multi-layer enhancement model; and showing that the overall quality rating of enhanced images is consistent with a combination of contrast enhancement and naturalness preservation. Two separate human observer evaluation studies were conducted on naturalness preservation and overall image quality. The results showed the proposed method outperformed four compared state-of-the-art enhancement methods.