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Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/2714
Title: A Bayesian approach for shadow extraction from a single image
Authors: Wu, Tai-Pang
Tang, Chi-Keung
Keywords: Bayesian methods
Feature extraction
Image texture
Poisson equation
Issue Date: Oct-2005
Citation: Proceedings 10th IEEE International Conference on Computer Vision, 17-21 October 2005, Beijing, China, part vol. 1, p. 480-487
Abstract: This paper addresses the problem of shadow extraction from a single image of a complex natural scene. No simplifying assumption on the camera and the light source other than the Lambertian assumption is used. Our method is unique because it is capable of translating very rough usersupplied hints into the effective likelihood and prior functions for our Bayesian optimization. The likelihood function requires a decent estimation of the shadowless image, which is obtained by solving the associated Poisson equation. Our Bayesian framework allows for the optimal extraction of smooth shadows while preserving texture appearance under the extracted shadow. Thus our technique can be applied to shadow removal, producing some best results to date compared with the current state-of-the-art techniques using a single input image. We propose related applications in shadow compositing and image repair using our Bayesian technique.
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URI: http://hdl.handle.net/1783.1/2714
Appears in Collections:CSE Conference Papers

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