Single-image shadow detection and removal using local colour constancy computation

被引:25
|
作者
Yuan, Xingsheng [1 ]
Ebner, Marc [2 ]
Wang, Zhengzhi [1 ]
机构
[1] Natl Univ Def Technol, Coll Elect & Automat, Changsha 410073, Hunan, Peoples R China
[2] Ernst Moritz Arndt Univ Greifswald, Inst Math & Informati, D-17487 Greifswald, Germany
基金
美国国家科学基金会;
关键词
image colour analysis; visual databases; single image shadow detection; single image shadow removal; local colour constancy computation; natural scenes; surface descriptor; termed colour-shade; physical considerations; image formation model; gradual colour surface variations; colour shade descriptor; condition random field model; shadow regions; image pixel; shadow detection databases;
D O I
10.1049/iet-ipr.2014.0242
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study is concerned with the problem of shadow detection and removal from single images of natural scenes. In this work, the authors propose a shadow detection method with a surface descriptor, termed colour-shade, which allows them to include the physical considerations derived from the image formation model capturing gradual colour surface variations. The authors incorporate a colour-shade descriptor into the condition random field model to find same illumination pairs and to obtain coherent shadow regions. The authors propose a shadow removal method using an improved local colour constancy computation, which uses anisotropic diffusion to estimate the illuminant locally for each image pixel in shadow. The authors evaluate their method on two shadow detection databases. The experimental results demonstrate that their shadow detection and removal method is state of the art.
引用
收藏
页码:118 / 126
页数:9
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