Please use this identifier to cite or link to this item:

Local color transfer via probabilistic segmentation by expectation-maximization

Authors Tai, YW
Jia, JY
Tang, CK View this author's profile
Issue Date 2005
Source IEEE Conference on Computer Vision & Pattern Recognition (CVPR) , 2005, p. 747-754
Summary 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 regions can be achieved, where the necessary intraregion and inter-region smoothness are enforced without losing original details. We demonstrate results on a variety ofapplications including image deblurring, enhanced color transfer, and colorizing gray scale images. Comparisons with previous methods are also presented.
ISSN 1063-6919
ISBN 0-7695-2372-2
Rights ©2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Language English
Format Conference paper
Access View full-text via DOI
View full-text via Web of Science
View full-text via Scopus
Files in this item:
File Description Size Format
cvpr05_postrefereed.pdf 1373376 B Adobe PDF