Data-driven image color theme enhancement

Baoyuan Wang, Yizhou Yu, Tien-Tsin Wong, Chun Chen, Ying-Qing Xu

Research output: Contribution to journalArticleResearchpeer-review

26 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalACM Transactions on Graphics
Volume29
Issue number6
DOIs
Publication statusPublished - 15 Dec 2010
Externally publishedYes

Keywords

  • Color Optimization
  • Color Theme
  • Histograms
  • Soft Segmentation
  • Texture Classes

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