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Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

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Page 1: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Colour vision

János Schanda Virtual Environments and Imaging

Technologies Laboratory

University of Pannonia

Page 2: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Overview

Human trichromacy The human retina Colour deficiencies

Path from the retina to the cortex Brightness versus luminance

The fifth light sensitive cell in the human retina

Page 3: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Visibility

Perceiving details

Rapid identification

Brightness/lightness

evaluation

Hue & colourfulness

evaluation

Page 4: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

The eye

Page 5: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

The structure of the eye

Page 6: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

The human eyeFovea: only cones, covered by the macula lutea, yellow pigmentation.Foveola: central parto of fovea, only L and M cones, blue colour blind.

Page 7: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Artist’s view of the structure of the foveal

retina

Page 8: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Light perception

Imaging the exterior world on the retina

The retina and its most sensitive part the fovea

The receptive cells

Page 9: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

The structure of the retina

Page 10: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Cones and rods

Page 11: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Distribution of rods and cones within the retina

Page 12: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Spectral sensitivity of the three cone types, logarithmic scale

-8

-7

-6

-5

-4

-3

-2

-1

0

1

350 450 550 650 750

wavelength, nm

log

co

ne

ac

tio

n s

en

sit

ivit

y

L-cone

M-cone

S-cone

Page 13: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Fundamental colour matching experiment

Wright and Guild experiments

Different fundamentals

Transformed to common basis

Page 14: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

R, G, B primary based CMFs

R: 1 unit, 700 nm

G: 4,5907 units, 546,1 nm

B: 0,0601 units, 435,8 nm

Page 15: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Background information

CIE 1931 2° standard colorimetric observer and Colour Matching Functions (CMFs) CIE 1924 spectral luminous efficiency

function CIE 1964 10° standard colorimetric

observer and CMFs

Page 16: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

CIE TC 1-36 report

Fundamental Chromaticity Diagram with Physiological Axes - Part 1: CIE 170:2006 L,M,S cone fundamentals Photopigment absorption spectrum

Macular pigment absorption Field size dependence

Page 17: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Sties-Burch colour matching functions

wavelength (nm)

tristimulus values

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

350 400 450 500 550 600 650 700 750 800 850

_

_

l

r (λ )

_g (λ )b (λ )

Page 18: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Macular pigment optical density

wavelength (nm)

Opt

ical

Den

sity

0.0

0.1

0.2

0.3

0.4

350 400 450 500 550 600

2o

10 o

Page 19: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Lens and ocular media optical density

wavelength (nm)

Opt

ical

Den

sity

0.0

0.5

1.0

1.5

2.0

2.5

350 400 450 500 550 600 650 700

Page 20: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Derived photopigment low density absorbance

wavelength (nm)

Opt

ical

Den

sity

0.0

0.5

1.0

1.5

2.0

2.5

350 400 450 500 550 600 650 700

Page 21: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Complete path of getting to the corneal level cone

fundamentals

Photopigment low density

spectral absorbance

Ai,o(L-pigment)()

Ai,o(M-pigment)()

Ai,o(S-pigment)( )

Cornea

Retina

2° cone fundamentals

l2(), m2(), s2()

Macularpigment o.d.

2 deg

Lenspigment

o.d.

Cone photopigment o.d.

2 deg

FittedCMFs

2 deg

10° cone fundamentals

l10(), m10(), s10()

Cone photopigment o.d. 10 deg

ReferenceCMFs

10 deg

Lenspigment

o.d.

Macularpigment o.d. 10 deg

Stiles & Burch

Photopigment low density

spectral absorbance

Ai,o(L-pigment)()

Ai,o(M-pigment)()

Ai,o(S-pigment)( )

Cornea

Retina

2° cone fundamentals

l2(), m2(), s2()

Macularpigment o.d.

2 deg

Lenspigment

o.d.

Cone photopigment o.d.

2 deg

FittedCMFs

2 deg

10° cone fundamentals

l10(), m10(), s10()

Cone photopigment o.d. 10 deg

ReferenceCMFs

10 deg

Lenspigment

o.d.

Macularpigment o.d. 10 deg

Stiles & Burch

Page 22: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

2° cone fundamentals

Page 23: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Spectral sensitivity of the three cone types, linear scale

Page 24: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Transformation to XYZ-like CMFs for the 2°observer(tentative equation!)

Page 25: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

CIE 2° and cone fundamental derived (CFD) 2° CMFs

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

350 400 450 500 550 600 650 700 750 800

wavelength, nm

tris

itm

.va

lue

s

x¯(λ)

y¯(λ)

z¯(λ)

xF¯(λ)

yF¯(λ)

zF¯(λ)

Page 26: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Standard and cone

fundamental

chromaticity diagram

(Insert: DE per

wavelength)

Page 27: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

D(u’,v’) differences if the CIE 2° observer is used or the tentative CMFs of CIE TC 1-36

Calculated chromaticities usingCIE 1931 2° CMFs

0,3

0,4

0,5

0,6

0,0 0,1 0,2 0,3 0,4 0,5 0,6

u'

v'

RGB LEDVisual averageBroad-band reference

#1

#2

#3

#4

#5

#7

#8#9#6

CIE 1931 2° CFD-CMF

1 0,025 0,011

2 0,038 0,013

3 0,025 0,010

4 0,013 0,005

5 0,003 0,002

6 0,002 0,003

7 0,017 0,009

8 0,002 0,003

9 0,006 0,004Dom. wavelength: 626 nm, 525 nm, 473 nm

Page 28: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

CIE u’,v’ differences in case of CIE 2°, TC1-36 2° (Fundamental CMFs) und modified

2° Őbserver (Mod.Fund. CMFs)

0,000

0,005

0,010

0,015

0,020

0,025

0,030

0,035

0,040

0,045

0,050

Sample #1

Sample #2

Sample #3

Sample #4

Sample #5

Sample #6

Sample #7

Sample #8

Sample #9

Chromaticity differences using different CMFs (CIE 1976 u'v')

CIE 1931 2° CMFsFundamental CMFsModified Fundamental CMFs

Page 29: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Retinal processing Cone vision -> foveal

vision Long wave -L- Medium wave -M- Short wave -S-

sensitive cones

New signals are created already at retinal level Receptor cells produce

analogue potential difference for excitation

At output (ganglion cell) level fireing frequency signal is produced

Page 30: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Antagonistic colour channels and the brightness/lightiness channel

Page 31: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

ON and OFF signals The ON centre

bipolar cell is activated by the cone signal

The OFF centre cell gets activated as the light

decreases. Differences in

the ganglion cell fireing rate

Page 32: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Receptive fields, functional diagram

Page 33: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Receptive fields

Page 34: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Neural signal generation H1 &H2: horizontal cells,

participate in the antagonistic signal processing

B: bipolar cells, participate in the centre/surrounding antagonistic process (ON and OFF cells)

G: ganglion cells MC: magnocellular (ON and

OFF cells) PC: parvocellular (2 ON and

OFF cells) KC: koniocellular (2 ON cells)

Page 35: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Neural pathway - 1

Achromatic channel: L + M cone signal Sensitive on edges, contrast Luminance like spectral responsivity

flicker photometry small step brightness comparison

Rapid signal transmission Neurons leading to magnocellular layers

Page 36: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Standardised visibility functions

0

0.2

0.4

0.6

0.8

1

1.2

350 400 450 500 550 600 650 700 750 800

wavelength, nm

rel.

sens

itivi

ty

V(l)

VM(l)

V´(l)

y(l)10

Page 37: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Neural pathways -2

Parvocellular: L-M cone signal Fine details, slow Red – green antagonistic structure

Koniocellular: S – L, M-S cone signals Slow Yellow – blue antagonistic structure

Page 38: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Way of the colour signal from the retina to the

brain

Page 39: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Lateral geniculate body

Page 40: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Chromatic adaptation

Received from Prof. Hunt

Page 41: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia
Page 42: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Parsing of information

Page 43: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Visual areas of the cortex

Page 44: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Brightness – luminance

L+M signals: luminance like All three cones participate in brightness

perception Possible rod contribution to brightness Intrinsically photosensitive Retinal Ganglion

Cells might contribute too by pupil diameter regulation

Rod vision -> scotopic and peripheral vision

Mesopic vision: interaction between rod and cone receptors

Page 45: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Brightness description

CIE supplementary system of photometry, CIE 200:2011

Helm holtz-Kohlrauscheffect

Purkinje effect

Equivalent luminance, Leq

a = 0.05 cd/m2, b = 2.24 cd/m2, k = 1.3, f(x,y)=Nakano (1999)Parameters:

a =L + a

L

(adaptation coefficient; achromatic)

Photopic luminance

L

Scotopicluminance

L'

(L') · (L) ·101-a a c

ac =L

1/2+ b

kL1/2

(adaptation coefficient; chromatic)

c =ac · f(x,y)

Cr/gCy/b

Scotopic system Photopic system

V'(λ )input z(λ )inputy(λ )inputx(λ )input

c = ac [ f(x,y) - 0.078]

Page 46: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Luminance and brightness

-20,00

0,00

20,00

40,00

60,00

80,00

100,00

120,00

140,00

160,00

400 500 600 700

wavelength, nm

rel.

re

sp. V(l)

Vb2(l)

Landolt1,2,4,6

Page 47: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Sp. sensitivity of different receptors

47

350 400 450 500 550 600 650 7000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Gall-Circl¯(λ)m¯(λ)s¯(λ)

wavelength, nm

rel.

sen

siti

vit

y,

arb

. u

nit

s

Page 48: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Binary – broad band match

Broad-band: tunable LED source (curtasy of Zumtobel) with 470 nm blue component

Two component: cyan + deep red LED

25 observers

48

400 450 500 550 600 650 7000.000.100.200.300.400.500.600.700.800.901.00

2LED Zumtobel

wavelength, nm

rel.

in

ten

sity

, arb

itr.

un

its

Page 49: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Matching point of binary-broad-band match

49

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.80

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

x

y

Page 50: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

View of the double booth

50

Non-fluorescent white paper placed on black background, no colour in field of view.

Page 51: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Relative power in the circadian-, S-cone and Rod sensitivity bands comapred to the luminous flux

51

LED source Circadian/lum.flux S-cone/lum.flux rod/lum.flux

2 LED combination 0,73 0,22 1,1

Zumtobel adjustable source

0,39 0,23 0,56

Results of brightness comparison of 2 LED and “Zumtobel” source illuminated samples

Number of Persons 4 (1<35Y,0>65Y)

15

(1<35Y,4>65Y)

6 (1<35,1>65Y)

Rel. brightness (2 LED/”Zumt.”

0,86 1,20 1,02

% st. dev. 2,1 9,9 3,1

Observers found chromatic mismatch for equal chromaticity and luminance setting (Instr. Syst. CAS 140CT+TOP100 radiance probe)

Page 52: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Visual acuity

Landolt-C investigation The fovea is also in the mesopic range V(l)

sensitive Subjective evaluation is mainly based on

foveal vision

Page 53: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Summary

Foveal task: V(l) Peripheral task: V´(l) Brightness evaluation:

Equivalent luminance

Page 54: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Colour deficiencies Dichromat

protanope deuteranope tritanope

Anomalic trichromat protanomal deuteranomal tritanomal

Monochromat cone monochromat rod monochromat

Page 55: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Normal trichromat

Page 56: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Dichromat

Red-green colour deficient: cone density normal, but has only S and M cones

Page 57: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Dichromat

Red-green colour deficient : cone denstiy only 35 % of normal, has only S and L cones.

Page 58: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Rod achromat

Congenital rod achromat

Page 59: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia
Page 60: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

1,00 % 0,02 %

Page 61: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

1,10 % 0,01 %

Page 62: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

0,002 % ? %

Page 63: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Basic forms of colour deficiency

Pro

tan

óp

iaD

eu

tera

pia

Tritanóp

ia

Page 64: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Ishihara test

8 % of males is colour deficient, in case of females it is only 0,4 %.

Page 65: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

With regard to the colour deficient!

Normal

Deuteranop

Old coloratio

n

Modern coloratio

n

Page 66: Colour vision János Schanda Virtual Environments and Imaging Technologies Laboratory University of Pannonia

Thanks for your kind attention!

This publication/research has been supported by the TÁMOP-4.2.2/B-10/1-2010-0025 project.