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 language | English |
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Pages (from-to) | 1-10 |
Number of pages | 10 |
Journal | ACM Transactions on Graphics |
Volume | 29 |
Issue number | 6 |
DOIs | |
Publication status | Published - 15 Dec 2010 |
Externally published | Yes |
Keywords
- Color Optimization
- Color Theme
- Histograms
- Soft Segmentation
- Texture Classes