User-aided single image shadow removal

Han Gong, Darren Cosker, Chuan Li, Matthew Brown

Research output: Contribution to conferencePaperpeer-review

12 Citations (SciVal)
194 Downloads (Pure)


This paper presents a novel user-aided method for texture preserving shadow removal from single images which only requires simple user input. Compared with the state-of-the-art, our algorithm addresses limitations in uneven shadow boundary processing and umbra recovery. We first detect an initial shadow boundary by growing a user specified shadow outline on an illumination-sensitive image. Interval-variable intensity sampling is introduced to avoid artefacts raised from uneven boundaries. We extract the initial scale field by applying local group intensity spline fittings around the shadow boundary. Bad intensity samples are replaced by their nearest alternatives based on a log-normal probability distribution of fitting errors. Finally, we use a gradual colour transfer to correct post-processing artefacts such as gamma correction and lossy compression. Compared with state-of-the-art methods, we offer highly user-friendly interaction, produce improved umbra recovery and improved processing given uneven shadow boundaries.
Original languageEnglish
Number of pages6
Publication statusPublished - 2013
Event2013 IEEE International Conference on Multimedia and Expo (ICME) - San Jose, California, USA United States
Duration: 14 Jul 201318 Jul 2013


Conference2013 IEEE International Conference on Multimedia and Expo (ICME)
Country/TerritoryUSA United States
CitySan Jose, California


  • arrays
  • estimation
  • image color analysis
  • image segmentation
  • lighting
  • optimization
  • splines (mathematics)
  • shadow removal
  • single image
  • user-aided

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Signal Processing


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