why is this hard to read. unrelated vs. related color unrelated color: color perceived to belong to...

Post on 19-Dec-2015

217 Views

Category:

Documents

1 Downloads

Preview:

Click to see full reader

TRANSCRIPT

Why is this hard to read

Unrelated vs. Related Color

• Unrelated color: color perceived to belong to an area in isolation (CIE 17.4)

• Related color: color perceived to belong to an area seen in relation to other colors (CIE 17.4)

Illusory contour

• Shape, as well as color, depends on surround

• Most neural processing is about differences

Illusory contour

CS 768 Color Science

• Perceiving color

• Describing color

• Modeling color

• Measuring color

• Reproducing color

Spectral measurement

• Measurement p() of the power (or energy, which is power x time ) of a light source as a function of wavelength

• Usually relative to p(560nm)

• Visible light 380-780 nm

350 400 450 500 550 600 650 700 75040

60

80

100

120

Spectral Distribution of daylight

Rel

ati

ve P

ow

er

400 450 500 550 600 650 7000

2

4

6

8

10

12

14

Normalized to 560 nm

leaf

flower

Rel

ati

ve P

ow

er

Spectra of a red flower and a green leaf

400 450 500 550 600 650 7000

0.2

0.4

0.6

0.8

Normalized to spectrometer max

leaf

flower

Abs

olu

te P

ow

er

Data from http://www.it.lut.fi/research/color/database/database.html

-5 -4 -3 -2 -1 0 1 2 3 4 50

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Retinal line spread function

retinal position

rela

tive

inte

nsit

y

Linearity

• additivity of response (superposition)

• r(m1+m2)=r(m1)+r(m2)

• scaling (homogeneity)• r(m)=r(m)• r(m1(x,y)+m2 (x,y))=

r(m1)(x,y)+r(m2)(x,y)= (r(m1)+r(m2))(x,y)

• r(m(x,y))=r(m)(x,y)

-5 0 50

0.5

1

1.5

2

-5 0 50

0.5

1

1.5

2

-5 0 50

0.5

1

1.5

2Superposition

-5 0 50

0.5

1

1.5

2

-5 0 50

0.5

1

1.5

2

-5 0 50

0.5

1

1.5

2

reti

nal i

nten

sity

mon

itor

inte

nsit

y

Non-linearity

0 10 20 30 40 50 60 70 80 90 100

0.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1

stimulus

resp

ons

e

adaptive architecture provides more sensitivity over smaller range

http://webvision.med.utah.edu/

Ganglion

Bipolar

Amacrine

Rod Cone

Epithelium

Optic nerve

Retinal cross section

Light

Horizontal

Visual pathways

• Three major stages– Retina

– LGN

– Visual cortex

– Visual cortex is further subdivided

http://webvision.med.utah.edu/Color.html

Optic nerve

• 130 million photoreceptors feed 1 million ganglion cells whose output is the optic nerve.

• Optic nerve feeds the Lateral Geniculate Nucleus approximately 1-1

• LGN feeds area V1 of visual cortex in complex ways.

Photoreceptors

• Cones - – respond in high (photopic) light– differing wavelength responses (3 types)– single cones feed retinal ganglion cells so give

high spatial resolution but low sensitivity– highest sampling rate at fovea

Photoreceptors

• Rods– respond in low (scotopic) light– none in fovea

• try to foveate a dim star—it will disappear

– one type of spectral response– several hundred feed each ganglion cell so give

high sensitivity but low spatial resolution

Luminance

• Light intensity per unit area at the eye

• Measured in candelas/m2 (in cd/m2)

• Typical ambient luminance levels (in cd/m2): – starlight 10-3

– moonlight 10-1

– indoor lighting 102

– sunlight 105

– max intensity of common CRT monitors 10^2 From Wandell, Useful Numbers in Vision Science

http://white.stanford.edu/~brian/numbers/numbers.html

Rods and cones

• Rods saturate at 100 cd/m2 so only cones work at high (photopic) light levels

• All rods have the same spectral sensitivity

• Low light condition is called scotopic

• Three cone types differ in spectral sensitivity and somewhat in spatial distribution.

Cones

• L (long wave), M (medium), S (short)– describes sensitivity curves.

• “Red”, “Green”, “Blue” is a misnomer. See spectral sensitivity.

350 400 450 500 550 600 650 7000

0.2

0.4

0.6

0.8

1

wavelength (nm)

Co

ne r

esp

ons

e

Cone Spectral Responses

350 400 450 500 550 600 650 7000

0.2

0.4

0.6

0.8

1

wavelength (nm)

Con

e r

esp

on

se

Cone Spectral Responses

Receptive fields

• Each neuron in the visual pathway sees a specific part of visual space, called its receptive field

• Retinal and LGN rf’s are circular, with opponency; Cortical are oriented and sometimes shape specific.

--

----

--

-+

-

-

On center rf Red-Green LGN rf

+

++ +

+

+

+

+

-

-

-

Oriented Cortical rf

Channels: Visual Pathways subdivided

• Channels• Magno

– Color-blind

– Fast time response

– High contrast sensitivity

– Low spatial resolution

• Parvo

– Color selective

– Slow time response

– Low contrast sensitivity

– High spatial resolution

• Video coding implications• Magno

– Separate color from b&w

– Need fast contrast changes (60Hz)

– Keep fine shading in big areas

– (Definition)

• Parvo

– Separate color from b&w

– Slow color changes OK (40 hz)

– Omit fine shading in small areas

– (Definition)

• (Not obvious yet) pattern detail can be all in b&w channel

350 400 450 500 550 600 650 7000

0.5

1

V'() V()

350 400 450 500 550 600 650 7000

0.5

1

wavelength (nm)

Con

e r

esp

on

se

Trichromacy

• Helmholtz thought three separate images went forward, R, G, B.

• Wrong because retinal processing combines them in opponent channels.

• Hering proposed opponent models, close to right.

Opponent Models

• Three channels leave the retina:– Red-Green (L-M+S = L-(M-S))– Yellow-Blue(L+M-S)– Achromatic (L+M+S)

• Note that chromatic channels can have negative response (inhibition). This is difficult to model with light.

350 400 450 500 550 600 650 700 750

-1

-0.5

0

0.5

1

1.5

2

wavelength (nm)

RedGreen L-M+S BlueYellow L+M-S

Achromatic L+M+.05*S

Schematic color opponent response

+- +

350 400 450 500 550 600 650 700 750

-1

-0.5

0

0.5

1

1.5

2

V()

wavelength (nm)

RedGreen L-M+S BlueYellow L+M-S

Achromatic L+M+.05*S

Schematic color opponent response

100

10

1.0

0.1

0.001

-1 0 1 2

Log Spatial Frequency (cpd)

Con

tras

t Sen

siti

vity

Luminance

Red-Green

Blue-Yellow

Color matching

• Grassman laws of linearity:()(((

• Hence for any stimulus s() and response

r(), total response is integral of s() r(), taken over all or approximately s()r()

Primarylights

Test light

Bipartitewhitescreen

Surround field

Test light Primary lights

Subject

Surround light

Color Matching

• Spectra of primary lights s1(), s2(), s3()

• Subject’s task: find c1, c2, c3, such thatc1s1()+c2s2()+c3s3()

matches test light.

• Problems (depending on si())

– [c1,c2,c3] is not unique (“metamer”)

– may require some ci<0 (“negative power”)

Color matching

• What about three monochromatic lights?• M() = R*R() + G*G() + B*B()• Metamers possible• good: RGB functions are like cone

response• bad: Can’t match all visible lights with any

triple of monochromatic lights. Need to add some of primaries to the matched light

Primarylights

Test light

Bipartitewhitescreen

Surround field

Test light Primary lights

Subject

Surround light

Color matching

• Solution: CIE XYZ basis functions

350 400 450 500 550 600 650 700 7500

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

z

y x

CIE 1931 standard colorimetric observer color matching functions

Tris

timul

us v

alue

wavelength (nm)

Color matching

• Note Y is V()

• None of these are lights

• Euclidean distance in RGB and in XYZ is not perceptually useful.

• Nothing about color appearance

350 400 450 500 550 600 650 700 750-0.5

0

0.5

1

1.5

2

2.5

3

3.5Stiles and Burch 1959 10-degree bipartite field color matching functions

primary lights at 645.2 nm 525.3 nmand 444.4 nm

b10() g10()

r10()

top related