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Mitsubishi Electric Research Laboratories Raskar 2007
Media Lab, MIT
Cambridge, MA
Less is More:Less is More:
Coded Computational PhotographyCoded Computational Photography
Ramesh Raskar
P r o j e c t o r
T a g s
P o s = 0
P o s = 2 5 5
MIT Media Lab
Camera Culture
Ramesh Raskar
Camera Culture
Motion Blurred Photo
Short Exposure Traditional MURA
Deblurred
Result
Captured
Single
Photo
Shutter
Banding Artifacts and
some spatial frequencies
are lost
Dark
and noisy
Blurring == Convolution
Traditional Camera: Shutter is OPEN: Box Filter
PSF == Sinc Function
ω
Sharp Photo Blurred Photo
Fourier
Transform
Flutter Shutter: Shutter is OPEN and CLOSED
Preserves High Spatial
Frequencies
Sharp Photo Blurred Photo
PSF == Broadband Function
Fourier
Transform
Flutter Shutter CameraFlutter Shutter Camera
Raskar, Agrawal, Tumblin [Siggraph2006]
LCD opacity switched
in coded sequence
Traditional
Coded
Exposure
Image of
Static
Object
Deblurred
Image
Deblurred
Image
Coded Exposure
Temporal 1-D broadband code:
Motion Deblurring
Coded Aperture
Spatial 2-D broadband mask:
Focus Deblurring
Coded Aperture CameraCoded Aperture Camera
The aperture of a 100 mm lens is modified
Rest of the camera is unmodified
Insert a coded mask with chosen binary pattern
In Focus Photo
LED
Out of Focus Photo: Open Aperture
Out of Focus Photo: Coded Aperture
Captured Blurred
Photo
Refocused on
Person
Less is MoreLess is More
Blocking Light == More InformationBlocking Light == More Information
Coding in TimeCoding in Time Coding in SpaceCoding in Space
Less is More ..Less is More ..
• Coded Exposure
– Motion Deblurring [2006]
• Coded Aperture
– Focus Deblurring [2007]
• Optical Heterodyning
– Light Field Capture [2007]
• Coded Spectrum
– Agile Wavelength Profile [2008]
• Coded Illumination
– Motion Capture [2007]
– Multi-flash: Shape Contours [2004]
P r o je c t o r
T a g s
P o s = 0
P o s = 2 5 5
Computational PhotographyComputational Photography
1. Epsilon Photography
– Low-level vision: Pixels
– Multi-photos by perturbing camera parameters
– HDR, panorama, …
– ‘Ultimate camera’
1. Coded Photography
– Single/few snapshot
– Reversible encoding of data
– Additional sensors/optics/illum
– ‘Scene analysis’ : (Consumer software?)
1. Essence Photography
– Beyond single view/illum
– Not mimic human eye
– ‘New art form’
Computational PhotographyComputational Photography
1. Epsilon Photography
– Low-level Vision: Pixels
– Multiphotos by perturbing camera parameters
– HDR, panorama
– ‘Ultimate camera’
1. Coded Photography
– Mid-Level Cues:
• Regions, Edges, Motion, Direct/global
– Single/few snapshot
• Reversible encoding of data
– Additional sensors/optics/illum
– ‘Scene analysis’
1. Essence Photography
– Not mimic human eye
– Beyond single view/illum
– ‘New artform’
Computational PhotographyComputational Photography
1. Epsilon Photography
– Multiphotos by varying camera parameters
– HDR, panorama
– ‘Ultimate camera’: (Photo-editor)
1. Coded Photography
– Single/few snapshot
– Reversible encoding of data
– Additional sensors/optics/illum
– ‘Scene analysis’ : (Next software?)
1. Essence Photography
– High-level understanding
• Not mimic human eye
• Beyond single view/illum
– ‘New artform’
Mask? Sensor
Mask
SensorMask? Sensor
Mask
Sensor
Mask? Sensor
4D Light Field from
2D Photo:
Heterodyne Light Field
Camera
Full Resolution Digital
Refocusing:
Coded Aperture Camera
Light Field Inside a CameraLight Field Inside a Camera
Lenslet-based Light Field cameraLenslet-based Light Field camera
[Adelson and Wang, 1992, Ng et al. 2005 ]
Light Field Inside a CameraLight Field Inside a Camera
Stanford Plenoptic CameraStanford Plenoptic Camera [Ng et al 2005][Ng et al 2005]
4000 × 4000 pixels ÷ 292 × 292 lenses = 14 × 14 pixels per lens
Contax medium format camera Kodak 16-megapixel sensor
Adaptive Optics microlens array 125μ square-sided microlenses
Digital RefocusingDigital Refocusing
[Ng et al 2005][Ng et al 2005]
Can we achieve this with aCan we achieve this with a MaskMask alone?alone?
Mask based Light Field Camera
Mask
Sensor
[Veeraraghavan, Raskar, Agrawal, Tumblin, Mohan, Siggraph 2007 ]
How to Capture
4D Light Field with
2D Sensor ?
What should be the
pattern of the mask ?
Radio Frequency HeterodyningRadio Frequency Heterodyning
Baseband Audio
Signal
Receiver: DemodulationHigh Freq Carrier
100 MHz
Reference
Carrier
Incoming
Signal
99 MHz
Optical HeterodyningOptical Heterodyning
Photographic
Signal
(Light Field)
Carrier Incident
Modulated
Signal
Reference
Carrier
Main LensObject Mask Sensor
Recovered
Light
Field
Software Demodulation
Baseband Audio
Signal
Receiver: DemodulationHigh Freq Carrier
100 MHz
Reference
Carrier
Incoming
Signal
99 MHz
Captured 2D Photo
Encoding due to
Mask
2D
FFT
Traditional Camera Photo
Heterodyne Camera Photo
Magnitude of 2D FFT
2D
FFT
Magnitude of 2D FFT
Computing 4D Light Field
2D Sensor Photo, 1800*1800 2D Fourier Transform, 1800*1800
2D
FFT
Rearrange 2D tiles into 4D planes
200*200*9*94D IFFT
4D Light Field
9*9=81 spectral copies
200*200*9*9
A Theory of Mask-Enhanced CameraA Theory of Mask-Enhanced Camera
Main LensObject Mask Sensor
•Mask == Light Field Modulator
•Intensity of ray gets multiplied by Mask
•Convolution in Frequency domain
fθ
fx
fθ0
fx0
Band-limited
Light Field
Sensor Slice – Fourier
Slice Theorem
Photo = Slice of Light Field in Fourier Domain
[Ren Ng, SIGGRAPH 2005]
How to Capture 2D Light Field with 1D Sensor ?
fθ
fx
fθ0
fx0
Band-limited
Light Field
Sensor Slice
Fourier Light Field Space
Extra sensor bandwidth cannot capture
extra dimension of the light field
fθ
fx
fθ0
fx0
Sensor
Slice
Extra sensor
bandwidth
fθ
fx
??????
??? ???
Solution: Modulation Theorem
Make spectral copies of 2D light field
fθ
fx
fθ0
fx0
Modulation
Function
fθ
Modulated Light Field
fx
fθ0
fx0
Modulation
Function
Sensor Slice captures entire Light Field
Demodulation to recover Light Field
fθ
fx
Reshape 1D Fourier Transform into 2D
1D Fourier Transform of Sensor Signal
fθ
fx
fθ0
fx0
Modulation Function == Sum of Impulses
Physical Mask = Sum of Cosines
1/f0
Mask Tile
Cosine Mask Used
Where to place the Mask?
Mask
Sensor
Mask
Sensor
Mask Modulation
Function Mask Modulation
Function
fx
fθ
Mask Sensor
Where to place the Mask?
Mask
Modulation
Functionfx
fθ
Captured 2D Photo
Encoding due to
Cosine Mask
Computing 4D Light Field
2D Sensor Photo, 1800*1800 2D Fourier Transform
2D
FFT
Rearrange 2D tiles into 4D planes
200*200*9*94D IFFT
4D Light Field
9*9=81 spectral copies
200*200*9*9
Digital Refocusing
Only cone in
focus
Captured Photo
Full resolution 2D image
of Focused Scene Parts
Captured
2D Photo
Image of White Lambertian
Plane
divide
Coding and Modulation in Camera Using MasksCoding and Modulation in Camera Using Masks
Mask? Sensor
Mask
Sensor
Mask
Sensor
Coded Aperture for
Full Resolution
Digital Refocusing
Heterodyne Light
Field Camera
Agile Spectrum Imaging
With Ankit Mohan, Jack Tumblin [Eurographics 2008]
C
B
A
A’
B’
C’
Pinhole
Lens L1
Prism or
Diffraction Grating
Lens L2
Sensor
Rainbow
Plane
C’
’
B’
’
A’
’
Scene
Rainbow Plane inside Camera
A’
B’
C’ λ
λ
λ
C’
’
B’
’
A’
’
tS
Lens L2
x
I
x
t
A’
B’
C’ λ
λ
λ
C’
’
B’
’
A’
’
tR
Lens L2
x
I
x
t
tS
Glare Reduction/Enhancement usingGlare Reduction/Enhancement using
4D Ray Sampling4D Ray Sampling
Captured Glare
Reduced
Glare
Enhanced
i
j
x
Sensor
u
Glare = low frequency noise in 2D
•But is high frequency noise in 4D
•Remove via simple outlier rejection
i
j
Sensor
i
j
x
Pin-hole array
mask
u
Mask based Light Field Camera
Mask
Sensor
Glare Reduction/Enhancement usingGlare Reduction/Enhancement using
4D Ray Sampling4D Ray Sampling
[Siggraph 2008][Siggraph 2008]
Captured Glare
Reduced
Glare
Enhanced
• 6D Display
• Multi-flash Camera
• Computational Photography
– Online Siggraph Course Notes
– Google: ‘Computational Photography’
Other ProjectsOther Projects
Coded Computational Photography
• Coded Exposure
– Motion Deblurring [2006]
• Coded Aperture
– Focus Deblurring [2007]
– Glare reduction [2008]
• Optical Heterodyning
– Light Field Capture [2007]
• Coded Illumination
– Motion Capture [2007]
– Multi-flash: Shape Contours [2004]
• Coded Spectrum
– Agile Wavelength Profile [2008]
• Epsilon->Coded->Essence Photography
http://raskar.info
Blind CameraBlind Camera
Sascha Pohflepp,
U of the Art, Berlin, 2006
Coded Computational Photography
• Coded Exposure
– Motion Deblurring [2006]
• Coded Aperture
– Focus Deblurring [2007]
– Glare reduction [2008]
• Optical Heterodyning
– Light Field Capture [2007]
• Coded Illumination
– Motion Capture [2007]
– Multi-flash: Shape Contours [2004]
• Coded Spectrum
– Agile Wavelength Profile [2008]
• Epsilon->Coded->Essence Photography
http://raskar.info

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Raskar Coded Opto Charlotte

Notas del editor

  1. “Photography is the art of exclusion” Rockwell
  2. Car result
  3. Low signal to noise ratio
  4. How is the blurred image formed? It’s a convolution with box filter
  5. Coded exposure makes the filter broadband
  6. Comparisons
  7. License plate example: Blur = 60 pixels Can you guess what the car make is ? How many think it is the Audi ? Actually it is a Folksvagon.
  8. Cannot handle edges in blur
  9. 2D result
  10. Reversibly encode all the information in this otherwise blurred photo
  11. The glint out of focus shows the unusual pattern.
  12. Difficult to argue that the worm is performing high quality deconvolution to form an image. But in our group we are setting up experiments by creating active lighting probe to understand how worms perform visual analysis.
  13. Talk about limitations: Colocated artifacts, color coherency, ref can’t be obtain by subtraction
  14. Stereo-pair is a simple example of coded photography. Many decomposition problems, direct/global, diffuse/specular,
  15. Inference and perception are important. Intent and goal of the photo is important. The same way camera put photorealistic art out of business, maybe this new artform will put the traditional camera out of business. Because we wont really care about a photo, merely a recording of light but a form that captures meaningful subset of the visual experience. Multiperspective photos. Photosynth is an example.
  16. Maybe all the consumer photographer wants is a black box with big red button. No optics, sensors or flash. If I am standing the middle of times square and I need to take a photo. Do I really need a fancy camera?
  17. The camera can trawl on flickr and retrieve a photo that is roughly taken at the same position, at the same time of day. Maybe all the consumer wants is a blind camera.