The first light field camera for the consumer market

Todor Georgiev and Andrew Lumsdaine

Lytro

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.

Origins

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

Implements microlens array approach to plenoptic imaging Lytro sensor: 1.4 micron pixels with 14 micron microlenses in

hex array

Basic Lytro design: Microlens array

Microlens arraysensor

8X optical zoomOptical focus

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 cameraonly 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)

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 focusThis result is based on our camera similar to Lytro:Georgiev, T., Lumsdaine, A., Depth of Field in Plenoptic Cameras, Eurographics 2009.

Analysis of plenoptic camera imaging

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

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 (anti-vignetting) 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.

Factory Calibration

Lytro: Modulation images

Lytro: Modulation images

"clock": { "zuluTime": "2012-03-27T05:24:30.000Z" }, "pixelPitch": 0.000001399999976158141876680929 }, "lens": { "infinityLambda": 7.0, "focalLength": 0.05131999969482421875, "zoomStep": 100, "focusStep": 832, "fNumber": 2.21000003814697265625, "temperature": 38.569305419921875, "temperatureAdc": 2504, "zoomStepperOffset": 2, "focusStepperOffset": -36,

Lytro metadata examples

"mla": { "tiling": "hexUniformRowMajor", "lensPitch": 0.00001389861488342285067432158, "rotation": -0.002579216146841645240783691406, "defectArray": [], "scaleFactor": { "x": 1.0, "y": 1.00024712085723876953125 },

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.