Empirical Inference
Taking a sharp photo at several megapixel resolution traditionally relies on high grade lenses. In this paper, we present an approach to alleviate image degradations caused by imperfect optics. We rely on a calibration step to encode the optical aberrations in a space-variant point spread function and obtain a corrected image by non-stationary deconvolution. By including the Bayer array in our image formation model, we can perform demosaicing as part of the deconvolution.
| Author(s): | Schuler, CJ. and Hirsch, M. and Harmeling, S. and Schölkopf, B. |
| Links: | |
| Number (issue): | 1 |
| Year: | 2011 |
| Month: | May |
| Day: | 0 |
| BibTeX Type: | Technical Report (techreport) |
| Digital: | 0 |
| Electronic Archiving: | grant_archive |
| Institution: | Max Planck Institute for Intelligent Systems, Tübingen, Germany |
BibTeX
@techreport{SchulerHHS2011,
title = {Non-stationary Correction of Optical Aberrations},
abstract = {Taking a sharp photo at several megapixel resolution traditionally
relies on high grade lenses. In this paper, we present an approach to alleviate
image degradations caused by imperfect optics. We rely on a calibration step
to encode the optical aberrations in a space-variant point spread function and
obtain a corrected image by non-stationary deconvolution. By including the
Bayer array in our image formation model, we can perform demosaicing as part
of the deconvolution.},
number = {1},
institution = {Max Planck Institute for Intelligent Systems, Tübingen, Germany},
month = may,
year = {2011},
author = {Schuler, CJ. and Hirsch, M. and Harmeling, S. and Sch{\"o}lkopf, B.},
month_numeric = {5}
}