This paper presents an image editing framework where users use reference images to indicate desired color edits. In our approach, users specify pairs of strokes to indicate corresponding regions in both the original and the reference image that should have the same color “style”. Within each stroke pair, a nonlinear constrained parametric transfer model is used to transfer the reference colors to the original. We estimate the model parameters by matching color distributions, under constraints that ensure no visual artifacts are present in the transfer result. To perform transfer on the whole image, we employ optimization methods to propagate the model parameters defined at each stroke location to spatially-close regions of similar appearance. This stroke-based formulation requires minimal user effort while retaining the high degree of user control necessary to allow artistic interpretations. We demonstrate our approach by performing color transfer on a number of image pairs varying in content and style, and show that our algorithm outperforms state-of-the-art color transfer methods on both user-controllability and visual qualities of the transfer results.
User Controllable Color Transfer / Xiaobo, An; Pellacini, Fabio. - In: COMPUTER GRAPHICS FORUM. - ISSN 0167-7055. - 29:2(2010), pp. 263-271. [10.1111/j.1467-8659.2009.01595.x]
User Controllable Color Transfer
PELLACINI, FABIO
2010
Abstract
This paper presents an image editing framework where users use reference images to indicate desired color edits. In our approach, users specify pairs of strokes to indicate corresponding regions in both the original and the reference image that should have the same color “style”. Within each stroke pair, a nonlinear constrained parametric transfer model is used to transfer the reference colors to the original. We estimate the model parameters by matching color distributions, under constraints that ensure no visual artifacts are present in the transfer result. To perform transfer on the whole image, we employ optimization methods to propagate the model parameters defined at each stroke location to spatially-close regions of similar appearance. This stroke-based formulation requires minimal user effort while retaining the high degree of user control necessary to allow artistic interpretations. We demonstrate our approach by performing color transfer on a number of image pairs varying in content and style, and show that our algorithm outperforms state-of-the-art color transfer methods on both user-controllability and visual qualities of the transfer results.File | Dimensione | Formato | |
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