Example-Based Color Stylization of Images
Youngha Chang, Suguru Saito, Keiji Uchikawa, Masayuki Nakajima
In ACM Transactions on Applied Perception, 2(3), July 2005.
Abstract: We describe a new computational approach to stylize the colors of an image by using a reference image. During processing, we take the characteristics of human color perception into account to generate more appealing results. Our system starts by classifying each pixel value into one of the basic color categories, derived from our psychophysical experiments. The basic color categories are perceptual categories that are universal to everyone, regardless of nationality or cultural background. These categories are used to provide restrictions on color transformations to avoid generating unnatural results. Our system then renders a new image by transferring colors from a reference image to the input image, based on these categorizations. To avoid artifacts due to the explicit clustering, our system defines fuzzy categorization when pseudocontours appear in the resulting image. We present a variety of results and show that our method performs a large, yet natural, color transformation without any sense of incongruity and that the resulting images automatically capture the characteristics of the colors used in the reference image.
Keyword(s): Basic color categories, color transfer, example-based
Article URL: http://doi.acm.org/10.1145/1077399.1077408
BibTeX format:
@article{Chang:2005:ECS,
  author = {Youngha Chang and Suguru Saito and Keiji Uchikawa and Masayuki Nakajima},
  title = {Example-Based Color Stylization of Images},
  journal = {ACM Transactions on Applied Perception},
  volume = {2},
  number = {3},
  pages = {322--345},
  month = jul,
  year = {2005},
}
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