Image Restoration Using Online Photo Collections

Kevin Dale, Micah K. Johnson, Kalyan Sunkavalli, Wojciech Matusik, Hanspeter Pfister

ICCV 2009 pp. 2217-2224

doi:10.1109/ICCV.2009.5459473 /iccv/2009/dale2009iccv-image/

Abstract

We present an image restoration method that leverages a large database of images gathered from the web. Given an input image, we execute an efficient visual search to find the closest images in the database; these images define the input's visual context. We use the visual context as an image-specific prior and show its value in a variety of image restoration operations, including white balance correction, exposure correction, and contrast enhancement. We evaluate our approach using a database of 1 million images downloaded from Flickr and demonstrate the effect of database size on performance. Our results show that priors based on the visual context consistently out-perform generic or even domain-specific priors for these operations.

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Cite

Text

Dale et al. "Image Restoration Using Online Photo Collections." IEEE/CVF International Conference on Computer Vision, 2009. doi:10.1109/ICCV.2009.5459473

Markdown

[Dale et al. "Image Restoration Using Online Photo Collections." IEEE/CVF International Conference on Computer Vision, 2009.](https://mlanthology.org/iccv/2009/dale2009iccv-image/) doi:10.1109/ICCV.2009.5459473

BibTeX

@inproceedings{dale2009iccv-image,
  title     = {{Image Restoration Using Online Photo Collections}},
  author    = {Dale, Kevin and Johnson, Micah K. and Sunkavalli, Kalyan and Matusik, Wojciech and Pfister, Hanspeter},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {2009},
  pages     = {2217-2224},
  doi       = {10.1109/ICCV.2009.5459473},
  url       = {https://mlanthology.org/iccv/2009/dale2009iccv-image/}
}