Global and Local Contrast Adaptive Enhancement for Non-Uniform Illumination Color Images

Abstract

Color images captured by digital devices may contain some non-uniform illuminations. Many enhancement methods produce undesirable results in the aspect of contrast improvement or naturalness preservation. A global and local contrast enhancement method is proposed for adaptively enhancing the non-uniform illumination images. Firstly, a novel global contrast adaptive enhancement algorithm obtains the global enhancement image. Secondly, a huepreserving local contrast adaptive enhancement algorithm produces the local enhancement image. Finally, a contrast-brightness-based fusion algorithm obtains the final result, which represents a trade-off between global contrast and local contrast. This method improves the visual quality and preserves the image naturalness. Experiments are conducted on a dataset including different kinds of non-uniform illumination images. Results demonstrate the proposed method outperforms the compared enhancement algorithms both qualitatively and quantitatively.

Cite

Text

Tian and Cohen. "Global and Local Contrast Adaptive Enhancement for Non-Uniform Illumination Color Images." IEEE/CVF International Conference on Computer Vision Workshops, 2017. doi:10.1109/ICCVW.2017.357

Markdown

[Tian and Cohen. "Global and Local Contrast Adaptive Enhancement for Non-Uniform Illumination Color Images." IEEE/CVF International Conference on Computer Vision Workshops, 2017.](https://mlanthology.org/iccvw/2017/tian2017iccvw-global/) doi:10.1109/ICCVW.2017.357

BibTeX

@inproceedings{tian2017iccvw-global,
  title     = {{Global and Local Contrast Adaptive Enhancement for Non-Uniform Illumination Color Images}},
  author    = {Tian, Qi-Chong and Cohen, Laurent D.},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2017},
  pages     = {3023-3030},
  doi       = {10.1109/ICCVW.2017.357},
  url       = {https://mlanthology.org/iccvw/2017/tian2017iccvw-global/}
}