NDLI: A Bayesian approach for shadow extraction from a single image

Content Provider	IEEE Xplore Digital Library
Author	Tai-Pang Wu Chi-Keung Tang
Copyright Year	2005
Description	Author affiliation: Vision & Graphics Group, Hong Kong Univ. of Sci. & Technol., China (Tai-Pang Wu; Chi-Keung Tang)
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 user-supplied 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.
Sponsorship	IEEE Comput. Soc. Tech. Comm. on Pattern Anal. and Machine Intelligence
Starting Page	480
Ending Page	487
File Size	777673
Page Count	8
File Format	PDF
ISBN	076952334X
ISSN	15505499
DOI	10.1109/ICCV.2005.4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian methods Cameras Lighting Light sources Computer vision Layout Optical computing Reflectivity Graphics Optimization methods
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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