Lytro
The first light field camera for the consumer market
Todor Georgiev and Andrew Lumsdaine
Origins

Ren’s Dissertation 2006
“Refocusing”

Levoy-Hanrahan “Light Field” (1996), Gortler et al. “Lumigraph” (1996),
Adelson’s “Plenoptic Function” (1991), etc.

Lippmann’s work on capturing radiation with array of lenslets “Integral
Photography” (1908). Nobel Prize (Color Photography)

Physical quantity: Radiance =
Energy density in 4D ray space.
11-2
Lytro Plenoptic Camera

Existing commercial platform for characterizing problem space and for new
algorithm development and exploration

Company founded in 2006 (as “Refocus Imaging”) to commercialize Ng’s
PhD thesis work at Stanford – handheld plenoptic camera

First camera available for sale October 2011

11Mpx CCD captures 11 “megarays”

Postprocessing accomplished on host

Originally Mac only

Now Mac + PC

Creates focal stack of images

Illusion of real time refocusing

New effects released Dec 4 2012

Perspective

Instagram-like effects
Basic Lytro design: Microlens array

Implements microlens array approach to plenoptic imaging

Lytro sensor: 1.4 micron pixels with 14 micron microlenses in hex array
sensor
Microlens array
Optical focus
8X optical zoom
Analysis of traditional camera imaging
The outside 3D world is mapped into the inside 3D world. Projective
transform mapping points to points, lines to lines, planes to planes. Infinity
treated projectivly. Points, lines and plane at infinity handled seemlesly.
Analysis of traditional camera imaging
The image plane (sensor) captures sharp all points that happen to be
mapped to its location. Everything else has certain amount of blur. This is
based on the mapping of rays to rays, points being defined as the
vertexes of pencils of rays.
Conventional camera image
In a conventional camera
only the area around the image
plane is in focus (DOF). The
rest is blurry.
Out of focus
In focus
Out of focus
Analysis of plenoptic camera imaging
If pixels are replaced by microlenses positioned at distance f from the
sensor, ray intensities would be directly recorded. Thus the plenoptic
camera captures the 4D image of ray intensities (the radiance), and not a
2D image. Full record of the radiance of a scene.
Analysis of plenoptic camera imaging
This approach (pixels replaced by microlenses) for recording ray direction
produces 1 pixel per microlens, which would be 0.1 megapixels for Lytro.
Our MTF measurements show 0.3 megapixels and in certain cases even
higher resolution. How is that possible? (see next)
Analysis of plenoptic camera imaging
The plenoptic camera as a relay system. Shaded area represents area of good
focusing of the microlenses (at Nyquist). In that area we can have full sensor
resolution rendering from each microimage. Mixing such microimages produces
the high final resolution that we observe. We call this “full resolution rendering.”
The unshaded area can render only 1 pixel per microimage, and is inside the
hyperfocal distance f ² / p from the microlenses, where p is pixel size. (This is
approximately 0.5 mm in Lytro)
Georgiev, T., Lumsdaine, A., Depth of Field in Plenoptic Cameras, Eurographics 2009.
Analysis of plenoptic camera imaging
In a plenoptic camera DOF is
extended, but the central part
can never be recovered in focus
from individual microimages
In focus
Out of focus
In focus
This result is based on our camera similar to Lytro:
Georgiev, T., Lumsdaine, A., Depth of Field in Plenoptic
Cameras, Eurographics 2009.
Plenoptic 2.0 camera
The plenoptic 2.0 camera as a relay system. Shaded area represents good
focusing of the microlenses, satisfying the lens equation. In that area we can have
full resolution rendering and super resolution that can be 4X better. The unshaded
area should be excluded. This approach is good for image capture close to the
microlenses, but it has lower DOF. Used by Raytrix.
Lumsdaine, A., Georgiev, T., The Focused Plenoptic Camera., ICCP 2009
Lytro: The Captured Image
Lytro: The Rendered Image
Lytro: The Rendered Image
More technical detail
Lytro: More technical detail
Lightfield Data for Algorithm Development


Lytro application stores three main sets of data (organized in sqlite db)

Camera calibration data / modulation images

Raw lightfield files

Processed lightfield files (focal stacks) are computed locally and stored
Raw lightfield files

Not demosaiced

Some meta information about the shot

JSON header plus raw 12-bit data
Factory Calibration

The RAW Microimages show vignetting, noise, random shift of microlenses, etc.
To correct, a calibration step is required as imperfections are camera specific.

Modulation images are included with each Lytro camera (12bit images with time
stamp). Calibration images summary:

•
60 modulation images are captured for each camera at manufacture time
(30 min based on file time stamp). Different lens settings, like focus, zoom,
exposure.
•
Two dark images at different exposure.
Our modulation images usage for Lytro rendering:
•
Divide the captured image by the corresponding modulation image (antivignetting) at similar parameters. Clean up pattern noise, dark noise.
•
Compute the true microimage centers. Use the new centers for rendering.
This is the most important calibration in our experience.
•
Possibly Lytro is using lens model to compute centers.
Lytro: Modulation images
Lytro: Modulation images
Lytro metadata examples
"clock": {
"mla": {
"zuluTime": "2012-03-27T05:24:30.000Z"
"tiling": "hexUniformRowMajor",
},
"lensPitch": 0.00001389861488342285067432158,
"rotation": -0.002579216146841645240783691406,
"pixelPitch": 0.000001399999976158141876680929
"defectArray": [],
},
"scaleFactor": {
"lens": {
"x": 1.0,
"infinityLambda": 7.0,
"y": 1.00024712085723876953125
"focalLength": 0.05131999969482421875,
},
"zoomStep": 100,
"focusStep": 832,
"fNumber": 2.21000003814697265625,
"temperature": 38.569305419921875,
"temperatureAdc": 2504,
"zoomStepperOffset": 2,
"focusStepperOffset": -36,
So for example, microlens pitch is 13.9um,
and the microlens array is estimated to have
rotation angle -0.00258 relative to the
sensor. Zoom step and focus step change
for each picture. Our calibration is done by
trying to match the image parameters with
calibration images having closest metadata.
Demo of rendering Lytro
Demo of rendering Lytro
Lytro MTF: Target 15 and 20cm from the camera
15cm
20cm
Compare with halftone printing by dithering
This effect is characteristic for 1.0 camera at the depth corresponding to the
microlenses. It’s the price we pay for extending depth of field / good refocusability.
Real world Lytro example
Real world Lytro example
Zoomed in refocusing
Zoomed in refocusing – note the dot artifacts
Microimages of constant color
Conclusion: Lytro and resolution of plenoptic cameras
Conclusion:
Lytro is the first light field camera for the consumer market.
It’s likely that Lytro renders images based on a version of the full resolution method,
generating much more than 1 pixel per microlens. The Lytro camera and application
appear to reproduce sensor resolution captured by each micro image. However due
to mixing of multiple views, final image resolution (under 1 megapixel) is far below
sensor resolution (11 megarays).
Typical numbers for full resolution rendering from plenoptic camera data are 10X -20X less than the sensor resolution. That’s for Lytro and for any other rendering.
This situation can be greatly improved with superresolution. Results with resolution
only 5X lower than that of the sensor have been demonstrated.
Lytro too have been able to generate much higher resolution than their current
rendering, in certain cases.