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Removing Shadows From Images using Retinex

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The Retinex Theory first introduced by Edwin Land forty years ago has been widely used for a range of applications. It was first introduced as a model of our own visual processing but has since been used to perform a range of image processing tasks including illuminant correction, dynamic range compression, and gamut mapping. In this paper we show how the theory can be extended to perform yet another image processing task: that of removing shadows from images. Our method is founded on a simple modification to the original, path based retinex computation such that we incorporate information about the location of shadow edges in an image. We demonstrate that when the location of shadow edges is known the algorithm is able to remove shadows effectively. We also set forth a method for the automatic location of shadow edges which makes use of a 1-d illumination invariant image proposed in previous work [1]. In this case the location of shadow edges is imperfect but we show that even so, the algorithm does a good job of removing the shadows.
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Document Type: Research Article

Publication date: January 1, 2002

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  • CIC is the premier annual technical gathering for scientists, technologists, and engineers working in the areas of color science and systems, and their application to color imaging. Participants represent disciplines ranging from psychophysics, optical physics, image processing, color science to graphic arts, systems engineering, and hardware and software development. While a broad mix of professional interests is the hallmark of these conferences, the focus is color. CICs traditionally offer two days of short courses followed by three days of technical sessions that include three keynotes, an evening lecture, a vibrant interactive (poster) papers session, and workshops. An endearing symbol of the meeting is the Cactus Award, given each year to the author(s) of the best interactive paper; there are also Best Paper and Best Student Paper awards.

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