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TitleA Computational Light Field Display for Correcting Visual Aberrations
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Page 1

A Computational Light Field Display for Correcting

Visual Aberrations

Fu-Chung Huang

Electrical Engineering and Computer Sciences
University of California at Berkeley

Technical Report No. UCB/EECS-2013-206

http://www.eecs.berkeley.edu/Pubs/TechRpts/2013/EECS-2013-206.html

December 15, 2013

Page 59

CHAPTER 5. MULTILAYER DISPLAYS 47

Camera photographs Using the same parameters as the previous simulation, a Canon EOS
Rebel T3 digital camera, with a Canon EF 50mm f/1.8 II lens, was separated by 100 cm from

the front layer of the prototype. The camera is focused at 16cm in front of the display, with the

minimum f-number setting of f/1.8, resulting in an aperture diameter of 2.8cm.

Figure 5.9 summarizes experimental results achieved with the multilayer LCD prototype. The

same three sample images are evaluated. As described in Section 5.3.2, three exposures are com-

bined to synthesize color images using the grayscale panels. Comparing Figure 5.9 with Figure 5.7

confirms the predicted contrast enhancement and elimination of ringing artifacts. For example, the

inset region of the bird appears brighter and with higher contrast using multilayer prefiltering,

rather than the prior single-layer prefiltering algorithm. Also note that the outline of the eye and

the black stripes appear with less distortion using multilayer prefiltering. Ringing artifacts, visible

on the left-hand side of the face of the blue toy, are eliminated with multilayer prefiltering.

target image without
correction

single-layer
pre-filtering

multilayer
pre-filtering

without correction
(inset)

single-layer
(inset)

multilayer
(inset)

Michelson contrast = 1.00
DRC = 1:1

Michelson contrast = 1.00
DRC = 1:1

Michelson contrast = 1.00
DRC = 1:1

Michelson contrast = 1.00
DRC = 1:1

Michelson contrast = 1.00
DRC = 1:1

Michelson contrast = 1.00
DRC = 1:1

Michelson contrast = 0.08
DRC = 11.48:1

Michelson contrast = 0.12
DRC = 7.80:1

Michelson contrast = 0.14
DRC = 6.98:1

Michelson contrast = 0.13
DRC = 4.16:1

Michelson contrast = 0.15
DRC = 3.56:1

Michelson contrast = 0.20
DRC = 2.95:1

Michelson contrast = 1.00
DRC = 0.94:1

Michelson contrast = 1.00
DRC = 0.94:1

Michelson contrast = 1.00
DRC = 0.94:1

Michelson contrast = 0.08
DRC = 11.48:1

Michelson contrast = 0.12
DRC = 7.80:1

Michelson contrast = 0.14
DRC = 6.98:1

Michelson contrast = 0.13
DRC = 4.16:1

Michelson contrast = 0.15
DRC = 3.56:1

Michelson contrast = 0.20
DRC = 2.95:1

Figure 5.9: Camera photographs of prefiltering results. With the same parameters as the simu-
lated experiments, the multilayer (two-layer) prefiltering has better image contrast and has no ob-

vious ringings. The additional ringing artifacts are due to spatially varying point spread functions,

spherical aberrations, non-circular camera aperture, and residuals due to the non-linear gamma

correction and diffraction.

Page 60

CHAPTER 5. MULTILAYER DISPLAYS 48

Experimental results also reveal limitations of the linear spatially invariant (LSI) model in-

troduced in Section 3.1. First, the medical display panels used in the prototype do not produce

a linear radiometric response; gamma compression was applied to the displayed images, with a

calibrated gamma value 2.2, to approximate a radiometrically linear display. Remaining radio-
metric non-linearities contribute to ringing artifacts in the experimental imagery. Second, the lens

produces a spatially-varying PSF, as analyzed by Kee et al. [2011]; as seen in the bottom left of

the currency image, differences between the modeled and experimental PSFs result in ringing arti-

facts in the periphery. However, the central region is well approximated by the defocused camera

model introduced in Section 3.1.1. The camera lens aperture, consisting of several blades, used in

the experiment does not produce a circular symmetric point spread function, and thus the optical

transfer functions are different. Finally, the Canon EF 50mm f/1.8 lens has some spherical aberra-

tions, which is not modeled in the current experiments; we will have more discussions about the

modeling of higher order aberrations in Chapter 8.3.

We quantitatively assess the received image using the Michelson contrast metric, given by the

ratio of the difference of the maximum and minimum values, divided by their sum. Michelson

contrast is increased by an average of 44% using multilayer prefiltering rather than single-layer
prefiltering. Following Section 4.1, prefiltering expands the dynamic range both above and below

the range of radiance values that are physically supported by the display. We quantify this effect by

evaluating the dynamic range compression (DRC) of the prefiltered images, given by the difference

of the maximum and minimum values before normalization using Equation 4.5. By convention,

the displayed normalized images always have a dynamic range of unity. For these examples, the

dynamic range is reduced by an average of 42%, enabling contrast to be enhanced with multilayer
prefiltering, despite normalization.

Video Data Prefiltering can also apply to video sequences. Without modifications, processing
each frame independently produces videos with rapid intensity variations, as shown in Figure 5.10.

We attribute this to the fact that normalization changes the mean received image value, due to

variations in the minimum and maximum values of the prefiltering images. For a pre-recorded se-

quence, perceived flashing can be removed by normalizing each frame by the global minimum and

maximum values of the prefiltered sequence, as shown in Figure5.11. For interactive or stream-

ing content, we propose applying an adaptive filter to recursively estimate a temporally smoothed

estimate of the necessary normalization range.

3

7

9
single-layer prefiltering

multilayer prefiltering

5

Figure 5.10: Dynamic range variations of prefiltering in a video sequence.

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