IET Image Processing · 2014 · 26 citations · 22 references
MedicineVision ScienceColor VisionComputer VisionDigital ImagingColor ConstancyDigital Image ProcessingImage RestorationLighting ModelsShading ModelsSurface ShadingAnisotropic DiffusionConstancy In Natural ScenesIlluminant EstimationImage Formation ModelsLocal Color ConstancyScene Illumination EstimationShadow AnalysisShadow Removal
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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A spatial processor model for object colour perception
Gershon Buchsbaum · Journal of the Franklin Institute · 1980 · 1.7K citations