colorimetric characterization models for lcd and …•lcd model requires measurement of full r,g,b...

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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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.

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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)

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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

˘

˚

˙ ˙ ˙

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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

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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

˘

˚

˙ ˙ ˙ ˙

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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

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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)

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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)

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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

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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

colorimetric characterization models for lcd and …•lcd model requires measurement of full r,g,b...

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