Transfer Efficiency and Depth Invariance in Computational Cameras
Proc. IEEE International Conference on Computational Photography, March 2010
Figure. Top: the transfer efficiency of the given lenses.
Bottom: the depth variance of the given lenses.
Abstract
Recent advances in computational cameras achieve extension of depth of field
by modulating the aperture of an imaging system, either spatially or temporally.
They are, however, accompanied by loss of image detail, the chief cause of which
is low and/or depth-varying frequency response of such systems. In this paper,
we examine the tradeoff between achieving depth invariance and maintaining high
transfer efficiency by providing a mathematical framework for analyzing the
transfer function of these computational cameras. Using this framework, we prove
mathematical bounds on the efficacy of the tradeoff. These bounds lead to
observations on the fundamental limitations of computational cameras. In
particular, we show that some existing designs are already near-optimal in our
metrics.
Paper (PDF; 473 KB):
Link
Supplement (PDF; 127 KB; Fast Computation of the OTFs for Various Computational Cameras):
Link
Slides: (PDF; 3.9 MB):
Link
Bibtex:
@inproceedings{Baek:2010:ASV:ICCPHOT.2010.5585098,
author = {Baek, Jongmin},
title = {Transfer efficiency and depth invariance in computational cameras},
booktitle = {Proceedings of IEEE International Conference on Computational Photography 2010},
issue_date = {March 2010},
month = {March},
year = {2010},
pages = {1-8},
doi = 10.1109/ICCPHOT.2010.5585098}
}