Skip to main content

Research Repository

Advanced Search

Aesthetic Enhancement via Color Area and Location Awareness

Yang, Bailin; Wang, Qingxu; Li, Frederick W.B.; Liang, Xiaohui; Wei, Tianxiang; Zhu, Changrui

Aesthetic Enhancement via Color Area and Location Awareness Thumbnail


Authors

Bailin Yang

Qingxu Wang

Xiaohui Liang

Tianxiang Wei

Changrui Zhu



Contributors

Y. Yang
Editor

A. D. Parakkat
Editor

B. Deng
Editor

S. T. Noh
Editor

Abstract

Choosing a suitable color palette can typically improve image aesthetic, where a naive way is choosing harmonious colors from some pre-defined color combinations in color wheels. However, color palettes only consider the usage of color types without specifying their amount in an image. Also, it is still challenging to automatically assign individual palette colors to suitable image regions for maximizing image aesthetic quality. Motivated by these, we propose to construct a contribution-aware color palette from images with high aesthetic quality, enabling color transfer by matching the coloring and regional characteristics of an input image. We hence exploit public image datasets, extracting color composition and embedded color contribution features from aesthetic images to generate our proposed color palettes. We consider both image area ratio and image location as the color contribution features to extract. We have conducted quantitative experiments to demonstrate that our method outperforms existing methods through SSIM (Structural SIMilarity) and PSNR (Peak Signal to Noise Ratio) for objective image quality measurement and no-reference image assessment (NIMA) for image aesthetic scoring.

Citation

Yang, B., Wang, Q., Li, F. W., Liang, X., Wei, T., & Zhu, C. (2022). Aesthetic Enhancement via Color Area and Location Awareness. In Y. Yang, A. D. Parakkat, B. Deng, & S. T. Noh (Eds.), . https://doi.org/10.2312/pg.20221247

Presentation Conference Type Conference Paper (Published)
Conference Name The 30th Pacific Conference on Computer Graphics and Applications, Pacific Graphics 2022
Start Date Oct 5, 2022
End Date Oct 8, 2022
Acceptance Date Aug 25, 2022
Publication Date 2022
Deposit Date Oct 31, 2022
Publicly Available Date Nov 1, 2022
DOI https://doi.org/10.2312/pg.20221247
Public URL https://durham-repository.worktribe.com/output/1135350
Related Public URLs https://diglib.eg.org/handle/10.2312/pg20221247

Files

Published Conference Proceeding (10.1 Mb)
PDF

Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
© 2022 The Author(s)
Eurographics Proceedings © 2022 The Eurographics Association.
Pacific Graphics (2022)
Y. Yang, A. D. Parakkat, B. Deng, and S.T. Noh (Editors)
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.






You might also like



Downloadable Citations