User-aided single image shadow removal


Gong, H., Cosker, D., Li, C. and Brown, M., 2013. User-aided single image shadow removal. In: 2013 IEEE International Conference on Multimedia and Expo (ICME), 2013-07-14 - 2013-07-18.

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    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.


    Item Type Conference or Workshop Items (Paper)
    CreatorsGong, H., Cosker, D., Li, C. and Brown, M.
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    URLURL Type
    Uncontrolled Keywordsarrays,estimation,image color analysis,image segmentation,lighting,optimization,splines (mathematics),shadow removal,single image,user-aided,computer graphics and computer-aided design,computer vision and pattern recognition,signal processing
    DepartmentsFaculty of Science > Computer Science
    Research CentresMedia Technology Research Centre
    Publisher Statement23.pdf: © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
    ID Code34978


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