Data-driven image color theme enhancement
Baoyuan Wang, Yizhou Yu, Tien-Tsin Wong, Chun Chen, Ying-Qing Xu
In ACM Transactions on Graphics, 29(6), December 2010.
Abstract: It is often important for designers and photographers to convey or enhance desired color themes in their work. A color theme is typically defined as a template of colors and an associated verbal description. This paper presents a data-driven method for enhancing a desired color theme in an image. We formulate our goal as a unified optimization that simultaneously considers a desired color theme, texture-color relationships as well as automatic or user-specified color constraints. Quantifying the difference between an image and a color theme is made possible by color mood spaces and a generalization of an additivity relationship for two-color combinations. We incorporate prior knowledge, such as texture-color relationships, extracted from a database of photographs to maintain a natural look of the edited images. Experiments and a user study have confirmed the effectiveness of our method.
Keyword(s): color optimization, color theme, histograms, soft segmentation, texture classes
Article URL: http://dx.doi.org/10.1145/1882261.1866172
BibTeX format:
@article{Wang:2010:DIC,
  author = {Baoyuan Wang and Yizhou Yu and Tien-Tsin Wong and Chun Chen and Ying-Qing Xu},
  title = {Data-driven image color theme enhancement},
  journal = {ACM Transactions on Graphics},
  volume = {29},
  number = {6},
  pages = {146:1--146:10},
  month = dec,
  year = {2010},
}
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