ML Anthology

Sensing Increased Image Resolution Using Aperture Masks

Ankit Mohan, Xiang Huang, Jack Tumblin, Ramesh Raskar
CVPR 2008
doi:10.1109/CVPR.2008.4587833 /cvpr/2008/mohan2008cvpr-sensing/

Abstract

We present a technique to construct increased-resolution images from multiple photos taken without moving the camera or the sensor. Like other super-resolution techniques, we capture and merge multiple images, but instead of moving the camera sensor by sub-pixel distances for each image, we change masks in the lens aperture and slightly defocus the lens. The resulting capture system is simpler, and tolerates modest mask registration errors well. We present a theoretical analysis of the camera and image merging method, show both simulated results and actual results from a crudely modified consumer camera, and compare its results to robust 'blind' methods that rely on uncontrolled camera displacements.

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Cite

Text

Mohan et al. "Sensing Increased Image Resolution Using Aperture Masks." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008. doi:10.1109/CVPR.2008.4587833

Markdown

[Mohan et al. "Sensing Increased Image Resolution Using Aperture Masks." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008.](https://mlanthology.org/cvpr/2008/mohan2008cvpr-sensing/) doi:10.1109/CVPR.2008.4587833

BibTeX

@inproceedings{mohan2008cvpr-sensing,
  title     = {{Sensing Increased Image Resolution Using Aperture Masks}},
  author    = {Mohan, Ankit and Huang, Xiang and Tumblin, Jack and Raskar, Ramesh},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2008},
  doi       = {10.1109/CVPR.2008.4587833},
  url       = {https://mlanthology.org/cvpr/2008/mohan2008cvpr-sensing/}
}