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

IET Image Processing(2015)

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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.
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关键词
gradual colour surface variations,local colour constancy computation,shadow detection databases,visual databases,condition random field model,image pixel,shadow regions,single image shadow detection,colour shade descriptor,natural scenes,surface descriptor,image formation model,termed colour-shade,single image shadow removal,physical considerations,image colour analysis
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