Naturalness Preserved Image Enhancement Using a Priori Multi-Layer Lightness Statistics

被引:62
|
作者
Wang, Shuhang [1 ]
Luo, Gang [1 ]
机构
[1] Mass Eye & Ear Harvard Med Sch, Schepens Eye Res Inst, Boston, MA 02114 USA
关键词
Image enhancement; naturalness preservation; lightness statistics; multi-layer; DYNAMIC HISTOGRAM EQUALIZATION; QUALITY ASSESSMENT; VISUAL-SYSTEM; COLOR IMAGES; CONTRAST; SPECIFICATION; ILLUMINATION; RETINEX;
D O I
10.1109/TIP.2017.2771449
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The 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. This paper 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.
引用
收藏
页码:938 / 948
页数:11
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