Computational Imaging and Superresolution |
Optoelectronics Center Director and Event Host Dr. Mike Fiddy |
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"...we plan to have a good mix of mathematicians, physicists, optical engineers and computer scientists at the workshop, both as participants and as speakers. There are several globally recognized keynote speakers attending..." |
June 10 - 12, 2008 - UNC Charlotte Campus
Computational Imaging and Superresolution Program PDF (8 MB)
Participants Group Photo
Recent advances in technologies for optical wavefront manipulation, optical detection, and digital post-processing have opened new possibilities for imaging systems in the visible and IR regimes. This opens up the possibility of developing imaging systems which differ in form factor and capabilities from traditional imaging systems and camera designs. The DARPA MONTAGE program pushed toward revolutionary imaging systems obtained by integration of the advancing capabilities of the individual optical, detection, and processing subsystems. This lead to an emerging capability for co-design and joint optimization of the optical, detection, and processing aspects of imaging systems. A parallel effort, IARPA’s PERIODIC program sought new functionality by making a single camera with a large number of lenslets capturing different information about the scene. This too lead to new ideas in what an imaging system is capable of and is pushing the integration of new microoptics technologies with new algorithms that compress data while extracting information of value. This workshop will bring together both hardware and software engineers as well as mathematicians and physicists who are actively working on the fundamental issues of information theory and light-matter interactions, to bring new ideas to the effort. Quite diverse communities that have not interacted before, such as the IEEE computational photography group and experts in fundamental limits to sub-wavelength optical superresolution will participate.
The main focus of MONTAGE was a next generation of ultra-small infrared cameras. For example, the Duke University team which will be represented at the workshop have demonstrated palm sized, ultra thin cameras that uses a grid of nine lenslets to capture nine different low resolution photographs. The lenses are 4 times thinner and 50 times smaller in mass than a conventional night vision camera. The images can also be encoded through the use of pupil plane or focal plane masks to further extract information of relevance from the data set. Software merges this information into a single digital super-resolution image of the scene. The software employs algorithms to correct for sensor distortion, noise and data losses that cause grainy, blurred images. An example is shown alongside. This research is a significant demonstration of the potential for advanced processing algorithms in compressed imaging applications. Continuing development is focusing on further reductions in size while functionality increases.
The basic idea of compressive imaging is that one can used advanced sampling and image interpolation algorithms to produce more image pixels than one measures. This concept is important for spectral imaging systems which could include 100 spectral channels per spatial pixel. Spectral imaging enables optical systems to identify molecular components in images for biomedical and security applications.
The workshop will consider the use of multi-aperture imaging for extended depth of field and increased FOV (field of view). New concepts employing lenslets on curved surfaces, mimicking some insect vision systems, are also being considered. Wavefront encoding and compressive imaging is important because of the flexibility in hardware design and new imaging modalities that result. Spectral estimation and superresolution algorithms are examples of a numerical technique involving prior knowledge and an optical procedure employing filters, that can be fused together in a number of different ways. Spectral imaging is a technique that generates a map of wavelength content per pixel, making it a useful tool in many applications including environmental remote sensing, military target discrimination, astrophysics and biomedical optics.
Schedule
| Monday, June 9th |
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Workshop participants arriving Monday Evening, June 9th, can attend a special Down Home Southern Welcome featuring a reception with hors d'oeuvres beginning at 5:30 and dinner at 8PM
| Tuesday, June 10th |
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Welcome
8.30 Welcome and Introductions - Mike Fiddy
Big Picture - Joe Mait + Ravi Athale
Overview everyone's interests - Mike, Ravi Athale, Joe Mait
Session 1
9.30 Optical Superresolution I - Colin Sheppard
10.30 Optical Superresolution II - Jim Fienup + Sapna Shroff
11.00 Fundamental limits to optical systems - Raphael Piestun
11.30 Coherence and subwavelength sensing - Aristide Dogariu
Lunch
12.00 lunch and posters
Session II
1.00 Computational Cameras - Shree Nayar
2.00 An overview of superresolution - Chuck Matson
2.30 Spectral estimation algorithms I - Charlie Byrne
3.00 Estimating the degree of polarization from intensity measurements - Tim Schulz
3.30 GST-PDFT - Markus Testorf
4.00 Light Field Sensing - Marc Levoy
5.00 Motion invariant photography - Fredo Durand
Reception
7:00 "Woodstock" Themed Reception and Dinner: Brainstorming Discussions
| Wednesday, June 11th |
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Session III
9.00 Biological & engineered information proc systs - Andreas Andreou
10.00 Less is More: Coded Computational Photography - Ramesh Raskar
11.00 New camera form factors - Jim Leger
12.00 From macro to micro: the challenge of miniaturization - Kenny Kubala
Lunch
12.30 lunch
Session IV
1.30 PERIODIC - Bob Plemmons/Sudhakar Prasad
2.00 COMP-I advances - Bob Gibbons/Nikos Pitsianis/Andrew Portnoy
2.30 Imaging demos
Contest
discussion and Futures Contest (powerpoint 2030 concepts)
Reception
6:00 "Around the World" Themed Reception
Speaker
After dinner speaker
Optical superresolution using compressive spectral imaging systems - Dave Brady
Vote
*Vote on 2030 concept papers!
| Thursday, June 12th |
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Session V
8.30 Imaging with coded apertures - Bill Freeman
9.30 Multiaperture imaging sensors - Keith Fife
10.30 Feature specific imaging - Mark Neifeld
11.30 Compressive imaging for wide-area persistent surveillance - Bob Muise
12.00 Single pixel camera - Kevin Kelly
Lunch
12.30 lunch
Open Forum: Challenges and Future Initiatives
1.30 Device Fabrication and Integration Eric Johnson (NSF)
2.00 Funding needs roundtable:
Dennis Healy (DARPA)
Eric Johnson (NSF)
Dr. Todd Du Bosq (Army Night Vision)
Tim Persons (IARPA)
Wrap Up
4.00 Wrap up
5.00 end
Reception
6:00 "Mardi Gras" Themed Reception and Dinner
continue discussions….for those who are left
Attendees
| Mehrdad Abolbashari - UNC Charlotte Andreas Andreou - Johns Hopkins Amit Ashok - CDM Optics Vasily Astratov - UNC Charlotte Ravi Athale - MITRE Charles Byrne - UMass Lowell Dave Brady - Duke University Larry Candell - MIT Lincoln Laboratory Aaron Cannistra - UNC Charlotte Shahab Chitchian - UNC Charlotte Angela Davies - UNC Charlotte Aristide Dogariu - CREOL, UCF Todd Du Bosq - Night Vision Fredo Durand - MIT Gary Euliss - MITRE Michael Feldman - Entrepreneur Jim Fienup - University of Rochester Keith Fife - Stanford Bill Freeman - MIT Dennis Healy - DARPA Eric Johnson - NSF/Optics Center Kevin Kelly - Rice U Kenny Kubala - CDM Optics Jim Leger - U Minnesota Sehoon Lim - Duke University Marc Levoy - Stanford |
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