4.4 Article

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

Journal

IET IMAGE PROCESSING
Volume 9, Issue 2, Pages 118-126

Publisher

INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-ipr.2014.0242

Keywords

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

Funding

  1. National Science Foundation of China [61174206]
  2. 973 project [2013CB329401]

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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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