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05.09.2022 - 09.09.2022, Iseolago hotel, Iseo, Italy.

News

MUST2022 Conference- a great success!
New scientific highlights- by MUST PIs Wörner, Chergui, and Richardson
FELs of Europe prize for Jeremy Rouxel- “Development or innovative use of advanced instrumentation in the field of FELs”
Ruth Signorell wins Doron prizefor pioneering contributions to the field of fundamental aerosol science
New FAST-Fellow Uwe Thumm at ETH- lectures on Topics in Femto- and Attosecond Science
International Day of Women and Girls in Science- SSPh asked female scientists about their experiences
New scientific highlight- by MUST PIs Milne, Standfuss and Schertler
EU XFEL Young Scientist Award for Camila Bacellar,beamline scientist and group leader of the Alvra endstation at SwissFEL
Prizes for Giulia Mancini and Rebeca Gomez CastilloICO/IUPAP Young Scientist Prize in Optics & Ernst Haber 2021
Nobel Prize in Chemistry awarded to RESOLV Member Benjamin List- for the development of asymmetric organocatalysis
NCCR MUST at Scientifica 2021- Lightning, organic solar cells, and virtual molecules
#NCCRWomen- NCCR MUST celebrates 50 years women’s right to vote in Switzerland

The Light Field Camera: Extended Depth of Field, Aliasing and Superresolution

Date Do, 27.11.2014 - Do, 27.11.2014
Time 11.15
Speaker Prof. Paolo Favaro, Institute of Computer Science and Applied Mathematics, University of Bern
Location Universität Bern, Institut für Angewandte Physik, Gebäude exakte Wissenschaften, Hörsaal B116, Sidlerstrasse 5, 3012 Bern
Program Portable light field cameras have demonstrated capabilities beyond conventional cameras. In a single snapshot, they enable digital image refocusing, i.e., the ability to change the camera focus after taking the snapshot, and 3D reconstruction. We show that they also achieve a larger depth of field than conventional cameras while maintaining the ability to reconstruct detail at high resolution. More interestingly, we show that their depth of field is essentially inverted compared to regular cameras. Crucial to the success of the light field camera is the way it samples the light field, trading off spatial vs. angular resolution, and how aliasing affects the light field. We present a novel algorithm that estimates a full resolution sharp image and a full resolution depth map from a single input light field image. The algorithm is formulated in a variational framework and it is based on novel image priors designed for light field images. We demonstrate the algorithm on synthetic and real images captured with our own light field camera, and show that it can outperform other computational camera systems.
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Link www.iap.unibe.ch
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