ML Anthology

Local Blur Estimation and Super-Resolution

Ming-Chao Chiang, Terrance E. Boult
CVPR 1997 pp. 821-826
doi:10.1109/CVPR.1997.609422 /cvpr/1997/chiang1997cvpr-local/

Abstract

Until now, all super-resolution algorithms have presumed that the images were taken under the same illumination conditions. This paper introduces a new approach to super-resolution, based on edge models and a local blur estimate, which circumvents these difficulties. The paper presents the theory and the experimental results using the new approach.

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Cite

Text

Chiang and Boult. "Local Blur Estimation and Super-Resolution." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997. doi:10.1109/CVPR.1997.609422

Markdown

[Chiang and Boult. "Local Blur Estimation and Super-Resolution." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997.](https://mlanthology.org/cvpr/1997/chiang1997cvpr-local/) doi:10.1109/CVPR.1997.609422

BibTeX

@inproceedings{chiang1997cvpr-local,
  title     = {{Local Blur Estimation and Super-Resolution}},
  author    = {Chiang, Ming-Chao and Boult, Terrance E.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1997},
  pages     = {821-826},
  doi       = {10.1109/CVPR.1997.609422},
  url       = {https://mlanthology.org/cvpr/1997/chiang1997cvpr-local/}
}