Self-Calibration of Optical Lenses

ICCV 2015

doi:10.1109/ICCV.2015.77 /iccv/2015/hirsch2015iccv-selfcalibration/

Abstract

Even high-quality lenses suffer from optical aberrations, especially when used at full aperture. Furthermore, there are significant lens-to-lens deviations due to manufacturing tolerances, often rendering current software solutions like DxO, Lightroom, and PTLens insufficient as they don't adapt and only include generic lens blur models. We propose a method that enables the self-calibration of lenses from a natural image, or a set of such images. To this end we develop a machine learning framework that is able to exploit several recorded images and distills the available information into an accurate model of the considered lens.

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Cite

Text

Hirsch and Scholkopf. "Self-Calibration of Optical Lenses." International Conference on Computer Vision, 2015. doi:10.1109/ICCV.2015.77

Markdown

[Hirsch and Scholkopf. "Self-Calibration of Optical Lenses." International Conference on Computer Vision, 2015.](https://mlanthology.org/iccv/2015/hirsch2015iccv-selfcalibration/) doi:10.1109/ICCV.2015.77

BibTeX

@inproceedings{hirsch2015iccv-selfcalibration,
  title     = {{Self-Calibration of Optical Lenses}},
  author    = {Hirsch, Michael and Scholkopf, Bernhard},
  booktitle = {International Conference on Computer Vision},
  year      = {2015},
  doi       = {10.1109/ICCV.2015.77},
  url       = {https://mlanthology.org/iccv/2015/hirsch2015iccv-selfcalibration/}
}