Data-Driven Image Color Theme Enhancement

被引:116
|
作者
Wang, Baoyuan [1 ]
Yu, Yizhou [1 ,2 ]
Wong, Tien-Tsin [3 ]
Chen, Chun [1 ]
Xu, Ying-Qing
机构
[1] Zhejiang Univ, Hangzhou, Zhejiang, Peoples R China
[2] Univ Illinois, Urbana, IL 61801 USA
[3] Chinese Univ Hong Kong, Hong Kong, Hong Kong, Peoples R China
来源
ACM TRANSACTIONS ON GRAPHICS | 2010年 / 29卷 / 06期
基金
美国国家科学基金会; 中国国家自然科学基金;
关键词
Color Theme; Color Optimization; Histograms; Soft Segmentation; Texture Classes; PREFERENCE; APPEARANCE; EMOTIONS;
D O I
10.1145/1866158.1866172
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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.
引用
收藏
页数:10
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