Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Computer Graphics and Applications
Colorization using optimization
ACM SIGGRAPH 2004 Papers
Local Color Transfer via Probabilistic Segmentation by Expectation-Maximization
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Image Retrieval With Relevance Feedback Based on Graph-Theoretic Region Correspondence Estimation
IEEE Transactions on Multimedia
Example-Based Color Transformation of Image and Video Using Basic Color Categories
IEEE Transactions on Image Processing
Hierarchical Color Correction for Camera Cell Phone Images
IEEE Transactions on Image Processing
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This paper proposes an automatic color transfer method based on multi-reference and graph-theoretic region correspondence estimation. When multiple high-quality reference images are available, our goal is to determine a set of best reference colors for transferring the color characteristics of the target image. Given a target image, we first employ content-based image retrieval technique to obtain a small number of relevant images as its multireference. Next, we represent each image in region level and determine the best-matched reference region for each target region. We propose to incorporate both region attribute and spatially adjacent relationships between regions into the region mapping criterion. Finally, we conduct color transfer between the best-matched region pairs in a de-correlated color space. Both subjective and objective measures of our experiments demonstrate that the proposed method outperforms the existing methods.