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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hasinoff, Samuel W. Kutulakos, Kiriakos N. Durand, Fredo Freeman, William T. |
| Copyright Year | 2009 |
| Description | Author affiliation: MIT CSAIL, USA (Hasinoff, Samuel W.; Durand, Fredo; Freeman, William T.) || University of Toronto, Canada (Kutulakos, Kiriakos N.) |
| Abstract | Capturing multiple photos at different focus settings is a powerful approach for reducing optical blur, but how many photos should we capture within a fixed time budget? We develop a framework to analyze optimal capture strategies balancing the tradeoff between defocus and sensor noise, incorporating uncertainty in resolving scene depth. We derive analytic formulas for restoration error and use Monte Carlo integration over depth to derive optimal capture strategies for different camera designs, under a wide range of photographic scenarios. We also derive a new upper bound on how well spatial frequencies can be preserved over the depth of field. Our results show that by capturing the optimal number of photos, a standard camera can achieve performance at the level of more complex computational cameras, in all but the most demanding of cases. We also show that computational cameras, although specifically designed to improve one-shot performance, generally benefit from capturing multiple photos as well. |
| Starting Page | 333 |
| Ending Page | 340 |
| File Size | 1533616 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424444205 |
| ISSN | 15505499 |
| DOI | 10.1109/ICCV.2009.5459269 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-09-29 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Photography Cameras Optical noise Optical sensors Uncertainty Spatial resolution Layout Monte Carlo methods Upper bound Frequency |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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