Wyble Talk - RIT

CIS

Industrial Associates M

eeting, May 12-13, 2003

MCSL

Colorimetric CharacterizationModels for LCD and DLPTM

Projectors

David R. Wyble [email protected]

Munsell Color Science LaboratoryChester F Carlson Center for Imaging Science

Rochester Institute of Technology54 Lomb Memorial Drive

Rochester, NY 14623

CIS


eeting, May 12-13, 2003

MCSLGoals for today

• Describe the differences and similarities of LCDand DLP projection technologies used in currentdata projectors

• Review various evaluation metrics and techniquesto compare projectors

• Propose a new characterization model for DLPprojectors

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eeting, May 12-13, 2003

MCSL

Technologies

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eeting, May 12-13, 2003

MCSLLCD System

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eeting, May 12-13, 2003

MCSLLCD Device

The LCD device operates using a change in thepolarity of the light.

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eeting, May 12-13, 2003

MCSLDLP System

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eeting, May 12-13, 2003

MCSLDLP Device

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eeting, May 12-13, 2003

MCSL

Metrics

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eeting, May 12-13, 2003

MCSLBrightness Uniformity

center

corners

inner

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eeting, May 12-13, 2003

MCSLBrightness Uniformity

50%

60%

70%

80%

90%

100%

LCDDLP

corner

inner

center = 100%

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eeting, May 12-13, 2003

MCSLImage Quality

LCD DLP

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eeting, May 12-13, 2003

MCSLLCD vs DLP Differences

• Number of color channels:

o LCD uses RGB

o DLP uses RGBW

• LCD tend to be more uniform in brightness

• DLP tend to have sharper images

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eeting, May 12-13, 2003

MCSLLCD vs DLP Similarities

• Resolution

• Color gamut

• Optics (zoom, etc)

The range of values for these specifications aresimilar among LCD and DLP projectors.

CIS


eeting, May 12-13, 2003

MCSLEvaluation Wrap-up

• There are several factors you should evaluate

o Cost (including bulb replacement)

o Brightness and image size

o Resolution

o Image quality

o Size and weight

• Specifications are great, but for each you should askyourself these questions

o “Is good enough for my needs?”

• Lastly, always ask “Do I like the image?”

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eeting, May 12-13, 2003

MCSL

Characterization Models

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eeting, May 12-13, 2003

MCSLProjector Characterization Overview

Projector Characterization

or

How can I make the projector display thecolor I choose?

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eeting, May 12-13, 2003

MCSLProjector Characterization Overview

• Users’ desire a particular color

• Projector accept only RBG (“device dependentcolor”)

• RGB does not correspond well to colors people see

• Critical for some issues (eg: logos, marketing)

• Nearly irrelevant for some issues (eg: technicalpresentations)

• Models presented here are not spatial. We assumea uniform image.

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eeting, May 12-13, 2003

MCSLDevice Characterization Basics

• “Device coordinates” are what we send to theprojector, RGB

• Color coordinates correspond to what we see,XYZ(“device independent color”)

• If the color coordinates of two colors are equal,we will perceive those colors as a match*.

• The goal of these device models will be topredict the output color coordinates (XYZ) for agiven set of input device coordinates (RGB)

CIS


eeting, May 12-13, 2003


DeviceCoordinates

(RGB)

ForwardModel

ColorCoordinates

(XYZ)

Inverse Model

DeviceCoordinates

(RGB)

ColorCoordinates

(XYZ)

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eeting, May 12-13, 2003


Inverse Model RGBXYZ

MeasuredXYZ

Project

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eeting, May 12-13, 2003


0 255Digital count

digital count

colo

rco

ordi

nate

Linearized digital count

colo

rco

ordi

nate

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eeting, May 12-13, 2003


digital count

colo

rco

ordi

nate

linearized digital count

colo

rco

ordn

ate

Lookuptable

†

XR XG XB

YR YG YB

ZR ZG ZB

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

¢ R ¢ G ¢ B

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

=

XYZ

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

CIS


eeting, May 12-13, 2003

MCSLLCD Characterization

†

XR XG XB

YR YG YB

ZR ZG ZB

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

-

XYZ

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

black

Ï

Ì Ô

Ó Ô

¸

˝ Ô

˛ Ô

¢ R ¢ G ¢ B

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

+

XYZ

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

black

=

XYZ

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

BlackCorrected

Matrix

LinearInputRGBs

Add Black

PredictedColor

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eeting, May 12-13, 2003

MCSL

0.0

0.2

0.4

0.6

0.8

1.0

0 32 64 96 128 160 192 224 256

Digital Count

Co

lor

Co

ord

inat

e (n

orm

aliz

ed)

white Y

LCD Characterization

Look up table comes directly frommeasured data, normalized to unity.

†

R = 96¢ R = 0.2

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eeting, May 12-13, 2003

MCSLLCD Characterization

Matrix and black correction comedirectly from measured data†

1399 1665 795780 3580 2700 107 4494

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

-

11.013.017.3

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

black

Ï

Ì Ô

Ó Ô

¸

˝ Ô

˛ Ô

¢ R ¢ G ¢ B

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

+

11.013.017.3

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

black

=

XYZ

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

†

XR XG XB

YR YG YB

ZR ZG ZB

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

-

XYZ

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

black

Ï

Ì Ô

Ó Ô

¸

˝ Ô

˛ Ô

¢ R ¢ G ¢ B

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

+

XYZ

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

black

=

XYZ

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

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eeting, May 12-13, 2003

MCSLLCD Model Results (Verification data)

DE94 is an indication of how perceptuallyclose the measured and predicted XYZ are.

0

5

10

15

20

25

0 0.4 0.8 1.2 1.6 2Color Difference (DE94)

Co

un

t

0

20

40

60

80

100

Cu

mu

lati

ve %Avg=0.5

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eeting, May 12-13, 2003

MCSLDLP Characterization

RGB ramp data cannot account forall the signal in the white ramp.

0

200

400

600

800

1000

1200

1400

1600

0 32 64 96 128 160 192 224 256

digital count

Col

or C

oord

inat

eR+G+B XR+G+B YR+G+B ZWhite XWhite YWhite Z

CIS


eeting, May 12-13, 2003


• Not as easy as the LCD

• We can measure the white ramp, but we know it ismore than just red, green, and blue.

• This violates our linearity assumption:

†

XR XG XB

YR YG YB

ZR ZG ZB

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

¢ R ¢ G ¢ B

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

†

XR XG XB XW

YR YG YB YW

ZR ZG ZB ZW

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

¢ R ¢ G ¢ B ¢ W

È

Î

Í Í Í Í

˘

˚

˙ ˙ ˙ ˙

CIS


eeting, May 12-13, 2003


†

¢ W = min(R,G,B)

There is a threshold, below which no white isadded. The threshold for our example DLPprojector is about 150 digital counts.

So, if:min(R,G,B)<150

W’=0, and there is no white added

CIS


eeting, May 12-13, 2003


These are ramp data of fixed R and G, varying Bfrom 0 to 255. Plot shows data after subtracting

the given contribution from R and G.

0

0.2

0.4

0.6

0.8

1

0 32 64 96 128 160 192 224 256Digital Count

Norm

aliz

ed C

olo

r Coord

inat

e

R=G=255

R=225, G=190

R=255, G=225

thresholdWhat cannot beaccounted for byR=225, G=190

Min(R,G,B)

What cannot beaccounted for byR=255, G=225

Min(R,G,B)

CIS


eeting, May 12-13, 2003


Look up tables for DLP model. White is“leftover” after subtracting RGB contribution.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 32 64 96 128 160 192 224 256Digital Count

Co

lor

Co

ord

inat

e (N

orm

aliz

ed)

Red XGreen YBlue ZW-(R+G+B)

CIS


eeting, May 12-13, 2003


†

XR XG XB XW

YR YG YB YW

ZR ZG ZB ZW

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

¢ R ¢ G ¢ B ¢ W

È

Î

Í Í Í Í

˘

˚

˙ ˙ ˙ ˙

+

XYZ

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

black

=

XYZ

È

Î

Í Í Í

˘

˚

˙ ˙ ˙

BlackCorrected

Matrix

LinearInputRGBs

Add Black

PredictedColor

CIS


eeting, May 12-13, 2003

MCSL

The DLP verification data were nearly all in the high intensityareas where the white addition assumptions are stressed.

0

40

80

120

160

200

240

0 0.5 1 1.5 2 2.5 3 3.5

Color Difference (DE94)

Co

un

t

0

20

40

60

80

100

Cu

mu

lati

ve %

DLP Model Results (Verification data)

Avg=1.5

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eeting, May 12-13, 2003

MCSLModel Results Summary

LCD model results

DLP model results

05

1015202530354045

0 0.5 1 1.5 2 2.5 3 3.5


Co

un

t

0

20

40

60

80

100

Cu

mu

lati

ve %

0

40

80

120

160

200

240

0 0.5 1 1.5 2 2.5 3 3.5


Co

un

t

0

20

40

60

80

100

Cu

mu

lati

ve %

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eeting, May 12-13, 2003

MCSLModel Summary

• Both models use measured data only. Noparameter estimation. (Except interpolatingthe look up table)

• LCD model requires measurement of fullR,G,B and complete white ramp. For ourexample LCD projector, better results werefound using full ramp measurements.

• DLP requires measurement of all fourramps

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eeting, May 12-13, 2003

MCSLModel Summary

• Both are very simple to implement

• LCD model performs very well

• DLP model performs acceptably

• Both models are satisfactory, especiallyconsidering additional variables:

o projection screen

o ambient room conditions

o viewing angles

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eeting, May 12-13, 2003

MCSLFuture Work

• Uncover and correct systematic trendsin the DLP model error.

• Perform additional measurements andimplement the model for the remainingDLP projectors.

• Submitted to 2003 IS&T Color ImagingConference

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eeting, May 12-13, 2003

MCSLThanks

This work was supported by theMunsell Color Science Laboratory.

Special thanks to graduate studentHongqin (Cathy) Zhang

Documents

Wyble Talk - RIT