VISUAL SIMULATING DICHROMATIC VISION IN CIE SPACE

Yinghua Hu

School of Computer Science

University of Central Florida

Keywords:

Dichromatic vision, Visual simulation.

Abstract:

Dichromatic vision is due to the loss of one of the three cone pigments: the L type in protanopes, the M type in

deuteranopes, and the S type in tritanopes. In this paper, we show that the dichromatic vision can be simulated

by applying transformation to image in CIE x, y chromaticity space. We base our work on the past experiments

on unilateral color blind (color blind in one eye) people which show that for protanopes and deuteranopes the

hue of 470 nm and 575 nm stimuli stay the same as that for normal eyes, and for tritanopes the hue of 485

nm and 660 nm are the same as that for normal eyes. We also assume that the curve between these anchored

stimuli points and D6500 standard white stimuli in the chromaticity diagram is quadratic. Our method saves

the steps for transformation of CIE chromaticity value to uniform chromaticity value or LMS value as required

in the previous work and still gets reasonable results.

1 INTRODUCTION

Normal color vision is trichromatic. It is initiated by

the absorption of photons in three types of photore-

ceptor cells in the retina: the short (S)-, middle (M)-,

and long (L)-wave sensitive cones, each of which con-

tains a different photopigment. The peak sensitivities

of these three photopigments lie in the long, middle

and short wavelength regions of the spectrum respec-

tively. Therefore any color stimulus can be speciﬁed

by the three cone responses.

Trichromacy, however, is not enjoyed by all. About

8% of the Caucasian male, 5% of the Asian male and

3% of the other male population suffer from color

blindness or color deﬁciency, only 0.5% of female

population is colorblind. Among colorblind popula-

tion, about one quarter is dichromatic, the rest are

anomalous trichromats, who have three classes of

photoreceptors, but do not perceive color as normal

trichromat do. Dichromacy is caused by the missing

of one of the three cone pigments, of the L type in

protanopes, the M type in deuteranopes, and the S

type in tritanopes. Compared with trichromatic vi-

sion, dichromatic vision entails a loss of hue discrim-

ination and results in a reduced color gamut. Dichro-

matic vision is a more restrictive form of defective

color vision than anomalous trichromats, so that color

schemes designed for dichromats can also be applied

for anomalous trichromats.

In this paper, we attempt to simulate for the normal

observer the color percept of dichromats. Our simula-

tion of dichromatic vision proceeds by applying trans-

formation in CIE x, y chromaticity coordinate space.

The simulation produces plausible results.

We believe that such simulation will enable artists,

web designers and graphics interface designers to

check how their work will appear to color deﬁcient

people. In entertainment industry, such kind of sim-

ulation can be necessary if the synthetic character is

color blind.

2 RESEARCH BACKGROUND

The history of simulation of the color perception of

dichromats begins with German writer and scientist

Goethe (1810). In Farbenlehre (Sharpe et al., 1999),

he included a reproduction of a small watercolor that

he painted to demonstrate how the landscape would

appear to those lacking the blue sensation.

Although researchers can check what colors the

dichromats confuse with by doing experiments, it is

impossible to relate this information to what they ac-

tually see instead. This problem has been overcome

Hu Y. (2006).

VISUAL SIMULATING DICHROMATIC VISION IN CIE SPACE.

In Proceedings of the First International Conference on Computer Graphics Theory and Applications, pages 92-97

DOI: 10.5220/0001351900920097

 SciTePress

by studying the vision of unilateral dichromats, (in-

dividuals born with one normal eye and one dichro-

matic eye). The past experiments suggest that both

protanopes and deuteranopes see the same blue at 470

nm and the same yellow at 575 nm as trichromats

(Judd, 1948; Graham and Hsia, 1958). Observations

also suggest that a blue-green at 485 nm and a red

at 660 nm have the same hue for the normal and tri-

tanopic eyes (Alpern et al., 1983).

Basing on these observations, (Meyer and Green-

berg, 1988) assume that color space of normal vision

collapses to a line called ”major axis” on the uni-

form chromaticity diagram for each of the three types

of dichromat. All the loci (straight lines) represent-

ing stimuli of the same dichromatic chromaticity will

converge to the same point in the chromaticity dia-

gram. That point is called confusion point and the

loci passing speciﬁed stimuli and confusion point is

called confusion line. Meyer and Greenberg compute

replacement color seen by dichromats by calculating

the intersection between the confusion line and the

major axis.

(Brettel et al., 1997) propose a replacement method

based on the same observations and the assumption

that neutrals for normals are perceived as neutrals

for dichromats. Firstly, they identify a neutral axis

which is a straight line connecting origin in the LMS

space and the brightest possible metamer of an equal-

energy stimulus. Secondly, they represent the surface

of the reduced stimuli of protanopes and deuteranopes

by the two half planes anchored by neutral axis and

475-nm and 575-nm locations in the LMS space, and

for tritanopes, they anchor the reduced stimuli sur-

face by neutral axis, 485-nm and 660-nm. Finally,

they compute a replacement stimulus for a stimulus

in trichromatic vision by projecting it onto the half

planes aforementioned by the direction parallel to the

missing fundamental axis. (Vi

enot et al., 1999; Vi

enot

and Brettel, 2001) simpliﬁed Brettel et al’s model by

replacing the two half planes with the diagonal plane

in the LMS space.

The CIE XYZ color space is based on direct mea-

surements of the human eye, and serves as the ba-

sis from which many other color spaces are deﬁned.

The study in this paper is based on the thought that

whether the simulation of dichromatic vision can be

done directly on CIE x, y chromaticity values.

3 ALGORITHM

Alike the assumption of major axis in the uniform

chromaticity by Meyer and Greenberg, our method

assumes that the CIE chromaticity space of normal

color vision collapses to a curve connecting the an-

chor points. The anchor points for this curve are de-

rived from the observations discussed in Section 2.

They are 470 nm and 575 nm for protanopes and

deuteranopes, and 485 nm and 660 nm for tritanopes.

We also assume that D6500 white stays as the same

hue in normal and dichromatic vision. So the color

space will collapse into a curve passing through the

anchor points and D6500. We use the Lagrange inter-

polation to get the other points on this hue curve.

The conversion matrix to transform from CIE XYZ

coordinates to RGB coordinates is known (Pharr and

Humphreys, 2004):

[XY Z

to RGB] =

3.2405 −1.5372 −0.4985

−0.9693 1.8760 0.0416

0.0556 −0.2040 1.0573

For a pixel in the picture, we ﬁrstly transform its

RGB value to XYZ coordinates by

= [RGB

to XY Z]

where

[RGB

to XY Z] = [XY Z to RGB]

−1

then transform XYZ coordinates to chromaticity

coordinates by:

x =

X + Y + Z

y =

X + Y + Z

In this algorithm, we use confusion point data from

(Wyszecki and Stiles, 1982):

= 0.747 x

= 1.080 x

= 0.171

= 0.253 y

= −0.080 y

= 0

For each chromaticity point A(x,y) in chromaticity

space, the chromaticity point A

(x’,y’) actually seen

by dichromats is found by intersecting the confusion

line passing A with the hue curve we get by interpo-

lation (See Figure 1).

The new chromaticity and original luminance is

then transformed back to RGB space:

′

∗ x

′

= Y Z

′

∗ z

′

= [XY Z

to RGB]

′

If the new color fell outside the monitor gamut (the

triangle in Figure 1), it is adjusted by holding its chro-

maticity constant and adjusting its luminance.

VISUAL SIMULATING DICHROMATIC VISION IN CIE SPACE

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

470

575

D65

protanopic

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

−0.1

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

470

575

D65

deuteranopic

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

485

660

D65

tritanopic

Figure 1: Curve of colors actually seen by dichromats and

adjustments made to a single chromaticity point to create a

dichromatic version of image. D65 represents D6500 white

and the triangle is the monitor gamut. Point P, D and T are

confusion points and the straight lines decided by confusion

points and A are confusion lines. A

, A

are the chro-

maticity points actually seen by protanopes, deuteranopes

and tritanopes on point A.

(a) Normal (b) Protanopic

Figure 2: Dichromatic versions of a testing image.

(a) Normal (b) Tritanopic

Figure 3: Tritanopic version of a testing image.

4 RESULTS

We implemented the algorithm in MATLAB. The

program takes the type of dichromat and a color

image as input, and generates as output an image

for the speciﬁed dichromat. We present the results

of our algorithm for standard images used for

colorblindness testing. In Figure 2, the original

Ishihara test image from Colorblind homepage

(http://www.colorvisiontesting.com/) is transformed

to protanopic and deuteranopic images where ”15” in

the normal version is recognized as ”13” or nothing.

Figure 3 shows an image from Wikipedia website

(http://en.wikipedia.org/wiki/Color

blindness) used

for testing tritanopia and its appearance in the

tritanopic vision generated by our algorithm.

GRAPP 2006 - COMPUTER GRAPHICS THEORY AND APPLICATIONS

A colorful picture and its appearance in dichro-

matic vision are shown in Figure 4.

5 DISCUSSION

To compare our algorithm and the previous work,

we run a test to convert the image in Figure 4(a) to

protanopic version using this algorithm, our imple-

mentation of Meyer’s algorithm and Brettel’s algo-

rithm. The resulting images are shown in Figure 5.

The test is done on a PC with a CPU of 2.00 GHZ

AMD Athlon XP 2400+ and 512 Mb memory. The

elapsed time for our algorithm, Meyer’s algorithm

and Brettel’s algorithm are respectively 87.5 s, 94.0 s

and 117.4 s. Our algorithm is more efﬁcient because

it does not require the procedure to transform color

value from CIE XYZ space to uniform chromaticity

value or LMS value as in Meyer or Brettel’s work.

6 CONCLUSION AND FUTURE

WORK

In this paper, we show that the simulation of dichro-

matic vision can be done by simple transformations

in CIE x, y chromaticity space. Our method saves the

steps for transformation of CIE chromaticity value to

uniform chromaticity value or LMS value as required

in the previous work and still gets reasonable results.

(Wachtler et al., 2004) propose that the color appear-

ance in dichromatic vision is richer than was previ-

ously thought. They insist that previous linear color

vision models fail to account for the richness of color

experience that dichromats enjoy and express. They

also propose a nonlinear model to simulate hue scal-

ing results. Using their model for realistic rendition of

dichromatic vision will be an interesting future work.

ACKNOWLEDGEMENTS

We thank Sumanta N. Pattanaik for his great help

since the inception of this research. We also thank

reviewers for their valuable comments.

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VISUAL SIMULATING DICHROMATIC VISION IN CIE SPACE

(a) Normal (b) Protanopic

Figure 4: A colorful picture and its appearance in dichromatic vision.

GRAPP 2006 - COMPUTER GRAPHICS THEORY AND APPLICATIONS

(a) Our algorithm (b) Meyer’s algorithm

Figure 5: The protanopic results of our algorithm and other algorithms applied on Figure 4(a).

VISUAL SIMULATING DICHROMATIC VISION IN CIE SPACE