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2005
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Local Color Transfer via Probabilistic Segmentation by Expectation-Maximization

9 years 11 months ago
Local Color Transfer via Probabilistic Segmentation by Expectation-Maximization
We address the problem of regional color transfer between two natural images by probabilistic segmentation. We use a new Expectation-Maximization (EM) scheme to impose both spatial and color smoothness to infer natural connectivity among pixels. Unlike previous work, our method takes local color information into consideration, and segment image with soft region boundaries for seamless color transfer and compositing. Our modified EM method has two advantages in color manipulation: First, subject to different levels of color smoothness in image space, our algorithm produces an optimal number of regions upon convergence, where the color statistics in each region can be adequately characterized by a component of a Gaussian Mixture Model (GMM). Second, we allow a pixel to fall in several regions according to our estimated probability distribution in the EM step, resulting in a transparency-like ratio for compositing different regions seamlessly. Hence, natural color transition across regio...
Yu-Wing Tai, Jiaya Jia, Chi-Keung Tang
Added 12 Oct 2009
Updated 29 Oct 2009
Type Conference
Year 2005
Where CVPR
Authors Yu-Wing Tai, Jiaya Jia, Chi-Keung Tang
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