Data-driven image color theme enhancement

Author:

Wang Baoyuan1,Yu Yizhou2,Wong Tien-Tsin3,Chen Chun1,Xu Ying-Qing4

Affiliation:

1. Zhejiang University

2. University of Illinois at Urbana-Champaign and Zhejiang University

3. The Chinese University of Hong Kong

4. Microsoft Research Asia

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.

Funder

Research Grants Council, University Grants Committee, Hong Kong

National Natural Science Foundation of China

Division of Information and Intelligent Systems

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design

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