Color Calibration of Multi-Projector Displays Through Automatic Optimization of Hardware Settings

Abstract

We describe a system that performs automatic, camera-based photometric projector calibration by adjusting hardware settings (e.g. brightness, contrast, etc.). The approach has two basic advantages over software-correction methods. First, there is no software interface imposed on graphical programs: all imagery displayed on the projector benefits from the calibration immediately, without render-time overhead or code changes. Secondly, the approach benefits from the fact that projector hardware settings typically are capable of expanding or shifting color gamuts (e.g. trading off maximum brightness versus darkness of black levels), something that software methods, which only shrink gamuts, cannot do. In practice this means that hardware settings can possibly match colors between projectors while maintaining a larger overall color gamut (e.g. better contrast) than software-only correction can. The prototype system is fully automatic. The space of hardware settings is explored by using a computer-controlled universal remote to navigate each projector's menu system. An off-the-shelf camera observes each projector's response curves. A cost function is computed for the curves based on their similarity to each other, as well as intrinsic characteristics, including color balance, black level, gamma, and dynamic range. An approximate optimum is found using a heuristic combinatoric search. Results show significant qualitative improvements in the absolute colors, as well as the color consistency, of the display.

Cite

Text

Steele et al. "Color Calibration of Multi-Projector Displays Through Automatic Optimization of Hardware Settings." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2009. doi:10.1109/CVPRW.2009.5204322

Markdown

[Steele et al. "Color Calibration of Multi-Projector Displays Through Automatic Optimization of Hardware Settings." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2009.](https://mlanthology.org/cvprw/2009/steele2009cvprw-color/) doi:10.1109/CVPRW.2009.5204322

BibTeX

@inproceedings{steele2009cvprw-color,
  title     = {{Color Calibration of Multi-Projector Displays Through Automatic Optimization of Hardware Settings}},
  author    = {Steele, R. Matt and Ye, Mao and Yang, Ruigang},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2009},
  pages     = {55-60},
  doi       = {10.1109/CVPRW.2009.5204322},
  url       = {https://mlanthology.org/cvprw/2009/steele2009cvprw-color/}
}