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Synthetic aperture confocal imaging PowerPoint PPT Presentation


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Synthetic aperture confocal imaging. Marc Levoy Billy Chen Vaibhav Vaish. Mark Horowitz Ian McDowall Mark Bolas. technologies large camera arrays large projector arrays camera–projector arrays. optical effects synthetic aperture photography synthetic aperture illumination

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Synthetic aperture confocal imaging

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Synthetic aperture confocal imaging

Marc Levoy

Billy Chen

Vaibhav Vaish

Mark Horowitz

Ian McDowall

Mark Bolas


technologies

large camera arrays

large projector arrays

camera–projector arrays

optical effects

synthetic aperture photography

synthetic aperture illumination

synthetic confocal imaging

applications

  • partially occluding environments

  • weakly scattering media

examples

foliage

murky water

Outline


Stanford Multi-Camera Array[Wilburn 2002]

  • 640 × 480 pixels ×30fps × 128 cameras

  • synchronized timing

  • continuous video streaming

  • flexible physical arrangement


Ways to use large camera arrays

  • widely spaced light field capture

  • tightly packed high-performance imaging

  • intermediate spacing synthetic aperture photography


Synthetic aperture photography


Synthetic aperture photography


Synthetic aperture photography


Synthetic aperture photography


Synthetic aperture photography


Synthetic aperture photography


Related work

  • not like synthetic aperture radar (SAR)

  • more like X-ray tomosynthesis

  • [Levoy and Hanrahan, 1996]

  • [Isaksen, McMillan, Gortler, 2000]


Example using 45 cameras


Synthetic pull-focus


Crowd scene


Crowd scene


Synthetic aperture photographyusing an array of mirrors

  • 11-megapixel camera

  • 22 planar mirrors

?


Synthetic aperture illumation


Synthetic aperture illumation

  • technologies

    • array of projectors

    • array of microprojectors

    • single projector + array of mirrors

  • applications

    • bright display

    • autostereoscopic display [Matusik 2004]

    • confocal imaging [this paper]


light source

pinhole

Confocal scanning microscopy


r

light source

pinhole

pinhole

photocell

Confocal scanning microscopy


Confocal scanning microscopy

light source

pinhole

pinhole

photocell


Confocal scanning microscopy

light source

pinhole

pinhole

photocell


[UMIC SUNY/Stonybrook]


→ 5 beams

→ 0 or 1 beam

Synthetic confocal scanning

light source


→ 5 beams

→ 0 or 1 beam

Synthetic confocal scanning

light source


d.o.f.

→ 5 beams

→ 0 or 1 beam

Synthetic confocal scanning

  • works with any number of projectors ≥ 2

  • discrimination degrades if point to left of

  • no discrimination for points to left of

  • slow!

  • poor light efficiency


Synthetic coded-apertureconfocal imaging

  • different from coded aperture imaging in astronomy

  • [Wilson, Confocal Microscopy by Aperture Correlation, 1996]


Synthetic coded-apertureconfocal imaging


Synthetic coded-apertureconfocal imaging


Synthetic coded-apertureconfocal imaging


Synthetic coded-apertureconfocal imaging

100 trials

→ 2 beams × ~50/100 trials ≈ 1

→ ~1 beam × ~50/100 trials ≈ 0.5


Synthetic coded-apertureconfocal imaging

100 trials

→ 2 beams × ~50/100 trials ≈ 1

→ ~1 beam × ~50/100 trials ≈ 0.5

floodlit

→ 2 beams

→ 2 beams

trials – ¼ × floodlit

→ 1 – ¼ ( 2 ) ≈ 0.5

→ 0.5 – ¼ ( 2 ) ≈ 0


Synthetic coded-apertureconfocal imaging

100 trials

→ 2 beams × ~50/100 trials ≈ 1

→ ~1 beam × ~50/100 trials ≈ 0.5

floodlit

→ 2 beams

→ 2 beams

trials – ¼ × floodlit

→ 1 – ¼ ( 2 ) ≈ 0.5

→ 0.5 – ¼ ( 2 ) ≈ 0

  • 50% light efficiency

  • any number of projectors ≥ 2

  • no discrimination to left of

  • works with relatively few trials (~16)


Synthetic coded-apertureconfocal imaging

100 trials

→ 2 beams × ~50/100 trials ≈ 1

→ ~1 beam × ~50/100 trials ≈ 0.5

floodlit

→ 2 beams

→ 2 beams

trials – ¼ × floodlit

→ 1 – ¼ ( 2 ) ≈ 0.5

→ 0.5 – ¼ ( 2 ) ≈ 0

  • 50% light efficiency

  • any number of projectors ≥ 2

  • no discrimination to left of

  • works with relatively few trials (~16)

  • needs patterns in which illumination of tiles are uncorrelated


Example pattern


Patterns with less aliasing


Implementation using an array of mirrors


Confocal imaging in scattering media

  • small tank

    • too short for attenuation

    • lit by internal reflections


Experiments in a large water tank

50-foot flume at Wood’s Hole Oceanographic Institution (WHOI)


Experiments in a large water tank

  • 4-foot viewing distance to target

  • surfaces blackened to kill reflections

  • titanium dioxide in filtered water

  • transmissometer to measure turbidity


Experiments in a large water tank

  • stray light limits performance

  • one projector suffices if no occluders


Seeing through turbid water

floodlit

scanned tile


[Ballard/IFE 2004]

Application tounderwater exploration

[Ballard/IFE 2004]


Research challenges in SAP and SAI

  • theory

    • aperture shapes and sampling patterns

    • illumination patterns for confocal imaging

  • optical design

    • How to arrange cameras, projectors,lenses, mirrors, and other optical elements?

    • How to compare the performance of different arrangements (in foliage, underwater,...)?


Challenges (continued)

  • systems design

    • multi-camera or multi-projector chips

    • communication in camera-projector networks

    • calibration in long-range or mobile settings

  • algorithms

    • tracking and stabilization of moving objects

    • compression of dense multi-view imagery

    • shape from light fields


Challenges (continued)

  • applications of confocal imaging

    • remote sensing and surveillance

    • shape measurement

    • scientific imaging

  • applications of shaped illumination

    • shaped searchlights for surveillance

    • shaped headlamps for driving in bad weather

    • selective lighting of characters for stage and screen


Computational imagingin other fields

  • medical imaging

    • rebinning

    • tomography

  • airborne sensing

    • multi-perspective panoramas

    • synthetic aperture radar

  • astronomy

    • coded-aperture imaging

    • multi-telescope imaging


Computational imagingin other fields

  • geophysics

    • accoustic array imaging

    • borehole tomography

  • biology

    • confocal microscopy

    • deconvolution microscopy

  • physics

    • optical tomography

    • inverse scattering


staff

Mark Horowitz

Marc Levoy

Bennett Wilburn

students

Billy Chen

Vaibhav Vaish

Katherine Chou

Monica Goyal

Neel Joshi

Hsiao-Heng Kelin Lee

Georg Petschnigg

Guillaume Poncin

Michael Smulski

Augusto Roman

collaborators

Mark Bolas

Ian McDowall

Guillermo Sapiro

funding

Intel

Sony

Interval Research

NSF

DARPA

The team


Related papers

  • The Light Field Video Camera

    Bennett Wilburn, Michael Smulski, Hsiao-Heng Kelin Lee, and Mark Horowitz

    Proc. Media Processors 2002, SPIE Electronic Imaging 2002

  • Using Plane + Parallax for Calibrating Dense Camera Arrays

    Vaibhav Vaish, Bennett Wilburn, Neel Joshi,, Marc Levoy

    Proc. CVPR 2004

  • High Speed Video Using a Dense Camera Array

    Bennett Wilburn, Neel Joshi, Vaibhav Vaish, Marc Levoy, Mark Horowitz

    Proc. CVPR 2004

  • Spatiotemporal Sampling and Interpolation for Dense Camera Arrays

    Bennett Wilburn, Neel Joshi, Katherine Chou, Marc Levoy, Mark Horowitz

    ACM Transactions on Graphics (conditionally accepted)


http://graphics.stanford.edu/papers/confocal


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