what is color? - vision...

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Computer Vision - A Modern Approach Set: Color Slides by D.A. Forsyth What is color? What do we mean by: Color of an object Color of a light Subjective color impression. Are all these notions the same? Wavelengths of light striking the eye are not sufficient or necessary for unique color impression. Surface color of an object is usually defined via its reflection function independent of any particular light’s spectral distribution Color of a light is usually defined in terms of its spectral distribution. Sources of variations in the amount of light at different wavelengths: Light could be produced in different amounts at different wavelengths (compare the sun and a fluorescent light bulb). Light could be differentially reflected (e.g. some pigments). It could be differentially refracted - (e.g. Newton’s prism) Wavelength dependent specular reflection - e.g. shiny copper penny (actually most metals). Florescence - light at invisible wavelengths is absorbed and reemitted at visible wavelengths.

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Page 1: What is color? - Vision Labsvision.psych.umn.edu/users/schrater/schrater_lab/courses/CompVis03/... · Slides by D.A. Forsyth What is color? ... eye are not sufficient or necessary

Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

What is color?• What do we mean by:

– Color of an object– Color of a light– Subjective color impression.– Are all these notions the same?

• Wavelengths of light striking theeye are not sufficient or necessaryfor unique color impression.

• Surface color of an object isusually defined via its reflectionfunction independent of anyparticular light’s spectraldistribution

• Color of a light is usually definedin terms of its spectral distribution.

• Sources of variations in the amountof light at different wavelengths:

– Light could be produced indifferent amounts at differentwavelengths (compare the sun anda fluorescent light bulb).

– Light could be differentiallyreflected (e.g. some pigments).

– It could be differentially refracted- (e.g. Newton’s prism)

– Wavelength dependent specularreflection - e.g. shiny copperpenny (actually most metals).

– Florescence - light at invisiblewavelengths is absorbed andreemitted at visible wavelengths.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Radiometry for colour

• All definitions are now “per unit wavelength”• All units are now “per unit wavelength”• All terms are now “spectral”• Radiance becomes spectral radiance

– watts per square meter per steradian per unit wavelength

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Defining Source Color: Black body radiators

• Construct a hot body with near-zero albedo (black body)– Easiest way to do this is to build a hollow metal object with a tiny

hole in it, and look at the hole.• The spectral power distribution of light leaving this object

is a simple function of temperature

• This leads to the notion of color temperature --- thetemperature of a black body that would look the same

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Measurements ofrelative spectral powerof sunlight, made by J.Parkkinen and P.Silfsten. Relativespectral power is plottedagainst wavelength innm. The visible range isabout 400nm to 700nm.The color names on thehorizontal axis give thecolor names used formonochromatic light ofthe correspondingwavelength --- the“colors of the rainbow”.

Violet Indigo Blue Green Yellow Orange Red

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Relative spectral powerof two standardilluminant models ---D65 models sunlight,andilluminant A modelsincandescent lamps.Relative spectral poweris plotted againstwavelength in nm. Thevisible range is about400nm to 700nm. Thecolor names on thehorizontal axis give thecolor names used formonochromatic light ofthe correspondingwavelength --- the“colors of the rainbow”.

Violet Indigo Blue Green Yellow Orange Red

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Measurements ofrelative spectral powerof four different artificialilluminants, made byH.Sugiura. Relativespectral power is plottedagainst wavelength innm. The visible range isabout 400nm to 700nm.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Spectral albedoes forseveral different leaves,with color namesattached. Notice thatdifferent colourstypically have differentspectral albedo, but thatdifferent spectralalbedoes may result inthe same perceivedcolor (compare the twowhites). Spectralalbedoes are typicallyquite smooth functions.Measurements byE.Koivisto.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

The appearance of colors

• Color appearance is stronglyaffected by (at least):

– other nearby colors,– adaptation to previous views– “state of mind”

• We show several demonstrations inwhat follows.

• Film color mode:View a colored surface

through a hole in a sheet, so thatthe color looks like a film in space;controls for nearby colors, and stateof mind.

• Other modes:– Surface color– Volume color– Mirror color– Illuminant color

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

The appearance of colors

• Hering, Helmholtz: Color appearance isstrongly affected by other nearbycolors, by adaptation to previous views,and by “state of mind”

• Film color mode: View acolored surface through a hole in asheet, so that the color looks like a filmin space; controls for nearby colors, andstate of mind.

– Other modes:• Surface colour• Volume colour• Mirror colour• Illuminant colour

• By experience, it is possible tomatch almost all colors, viewed infilm mode using only three primarysources - the principle oftrichromacy.

– Other modes may have moredimensions

• Glossy-matte• Rough-smooth

• Most of what follows discussesfilm mode.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Munker-White Illusion

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Simutaneous Contrast Illusion

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Paint or Shading?

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Why specify color numerically?

• Accurate color reproduction iscommercially valuable

– Many products are identified bycolor (“golden” arches;

• Few color names are widelyrecognized by English speakers -

– About 10; other languages havefewer/more, but not many more.

– It’s common to disagree onappropriate color names.

• Color reproduction problemsincreased by prevalence of digitalimaging - eg. digital libraries of art.

– How do we ensure that everyonesees the same color?

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Color matching experiments - I

• Show a split field to subjects; one side shows the lightwhose color one wants to measure, the other a weightedmixture of primaries (fixed lights).

• Each light is seen in film color mode.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Color matching experiments - II

• Many colors can be represented as a mixture of A, B, C• write

M=a A + b B + c C where the = sign should be read as “matches”• This is additive matching.• Gives a color description system - two people who agree

on A, B, C need only supply (a, b, c) to describe a color.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Subtractive matching

• Some colors can’t be matched like this:instead, must write

M+a A = b B+c C• This is subtractive matching.• Interpret this as (-a, b, c)• Problem for building monitors: Choose R, G, B such

that positive linear combinations match a large set ofcolors

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

The principle of trichromacy

• Experimental facts:– Three primaries will work for most people if we allow subtractive

matching• Exceptional people can match with two or only one primary.• This could be caused by a variety of deficiencies.

– Most people make the same matches.• There are some anomalous trichromats, who use three

primaries but make different combinations to match• These matches can be used to determine the genetics of their

photopigments.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Grassman’s Laws

• For colour matches made in film colour mode:– symmetry: U=V <=>V=U– transitivity: U=V and V=W => U=W– proportionality: U=V <=> tU=tV– additivity: if any two (or more) of the statements

U=V,W=X,(U+W)=(V+X) are true, then so is the third

• These statements are as true as any biological law. Theymean that color matching in film color mode is linear.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Linear color spaces

• A choice of primaries yields alinear color space --- thecoordinates of a color are givenby the weights of the primariesused to match it.

• Choice of primaries isequivalent to choice of colorspace.

• RGB: primaries aremonochromatic energies are645.2nm, 526.3nm, 444.4nm.

• CIE XYZ: Primaries areimaginary, but have otherconvenient properties. Colorcoordinates are (X,Y,Z), whereX is the amount of the Xprimary, etc.– Usually draw x, y, where

x=X/(X+Y+Z)y=Y/(X+Y+Z)

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Color matching functions

• Choose primaries, say A, B, C• Given energy function,

what amounts of primaries willmatch it?

• For each wavelength, determinehow much of A, of B, and of Cis needed to match light of thatwavelength alone.

• These are colormatchingfunctions

a(l)b(l )c(l )

E(l) Then our match is:

a(l)E(l)dl Ú{ }A +

b(l)E(l)dlÚ{ }B +

c(l)E(l)dlÚ{ }C

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

RGB: primaries aremonochromatic, energies are645.2nm, 526.3nm, 444.4nm.Color matching functions havenegative parts -> some colorscan be matched onlysubtractively.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

CIE XYZ: Colormatching functions arepositive everywhere, butprimaries are imaginary.Usually draw x, y, wherex=X/(X+Y+Z)

y=Y/(X+Y+Z)

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Color receptors

• Principle of univariance:cones give the same kind ofresponse, in different amounts,to different wavelengths. Theoutput of the cone is obtainedby summing over wavelengths.Responses are measured in avariety of ways (comparingbehaviour of color normal andcolor deficient subjects).

• All experimental evidencesuggests that the response of thek’th type of cone can be writtenas

where is the sensitivityof the receptor and spectralenergy density of the incominglight.

rÚ k(l)E(l)dl

rk (l)

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Color receptors• Plot shows relative sensitivity

as a function of wavelength, forthe three cones. The S (forshort) cone responds moststrongly at short wavelengths;the M (for medium) at mediumwavelengths and the L (forlong) at long wavelengths.

• These are occasionally called B,G and R cones respectively, butthat’s misleading - you don’tsee red because your R cone isactivated.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Simpler if we discretize frequency

E(l)

l

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

What does color matching do?

Choose f1

f2

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Then the combined primaries yields :

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

A qualitative rendering ofthe CIE (x,y) space. Theblobby region representsvisible colors. There aresets of (x, y) coordinatesthat don’t represent realcolors, because theprimaries are not real lights(so that the color matchingfunctions could be positiveeverywhere).

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

A plot of the CIE (x,y)space. We show thespectral locus (the colorsof monochromaticlights) and the black-body locus (the colors ofheated black-bodies). Ihave also plotted therange of typicalincandescent lighting.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Non-linear colour spaces

• HSV: Hue, Saturation, Value are non-linear functions ofXYZ.– because hue relations are naturally expressed in a circle

• Uniform: equal (small!) steps give the same perceivedcolor changes.

• Munsell: describes surfaces, rather than lights - lessrelevant for graphics. Surfaces must be viewed underfixed comparison light

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Computer Vision - A Modern ApproachSet: Color

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HSV hexcone

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Uniform color spaces

• McAdam ellipses (next slide) demonstrate that differencesin x,y are a poor guide to differences in color

• Construct color spaces so that differences in coordinatesare a good guide to differences in color.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Variations in color matches on a CIE x, y space. At the center of the ellipse is the color of atest light; the size of the ellipse represents the scatter of lights that the human observers testedwould match to the test color; the boundary shows where the just noticeable difference is.The ellipses on the left have been magnified 10x for clarity; on the right they are plotted toscale. The ellipses are known as MacAdam ellipses after their inventor. The ellipses at thetop are larger than those at the bottom of the figure, and that they rotate as they move up.This means that the magnitude of the difference in x, y coordinates is a poor guide to thedifference in color.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

CIE u’v’ which is aprojective transformof x, y. We transformx,y so that ellipses aremost like one another.Figure shows thetransformed ellipses.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Color receptors and color deficiency

• Trichromacy is justified - incolor normal people, there arethree types of color receptor,called cones, which vary intheir sensitivity to light atdifferent wavelengths (shownby molecular biologists).

• Deficiency can be caused byCNS, by optical problems in theeye, or by absent receptor types– Usually a result of absent

genes.

• Some people have fewer thanthree types of receptor; mostcommon deficiency is red-greencolor blindness in men.

• Color deficiency is lesscommon in women; red andgreen receptor genes are carriedon the X chromosome, andthese are the ones that typicallygo wrong. Women need twobad X chromosomes to have adeficiency, and this is lesslikely.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Adaptation phenomena

• The response of your colorsystem depends both on spatialcontrast and what it has seenbefore (adaptation)

• This seems to be a result ofcoding constraints --- receptorsappear to have an operatingpoint that varies slowly overtime, and to signal some sort ofoffset. One form of adaptationinvolves changing thisoperating point.

• Common example: walk insidefrom a bright day; everythinglooks dark for a bit, then takesits conventional brightness.

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

Viewing coloured objects

• Assume diffuse+specular model

• Specular– specularities on dielectric

objects take the colour of thelight

– specularities on metals can becoloured

• Diffuse– colour of reflected light

depends on both illuminant andsurface

– people are surprisingly good atdisentangling these effects inpractice (colour constancy)

– this is probably where some ofthe spatial phenomena incolour perception come from

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When one views a coloredsurface, the spectralradiance of the lightreaching the eye dependson both the spectralradiance of the illuminant,and on the spectral albedoof the surface. We’reassuming that camerareceptors are linear, likethe receptors in the eye.This is usually the case.

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Slides by D.A. Forsyth

Subtractive mixing of inks

• Inks subtract light from white,whereas phosphors glow.

• Linearity depends on pigmentproperties– inks, paints, often hugely non-

linear.• Inks: Cyan=White-Red,

Magenta=White-Green,Yellow=White-Blue.

• For a good choice of inks, andgood registration, matching islinear and easy

• eg. C+M+Y=White-White=BlackC+M=White-Yellow=Blue

• Usually require CMY andBlack, because colored inks aremore expensive, andregistration is hard

• For good choice of inks, there isa linear transform betweenXYZ and CMY

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Slides by D.A. Forsyth

Finding Specularities

• Assume we are dealing with dielectrics– specularly reflected light is the same color as the source

• Reflected light has two components– diffuse– specular– and we see a weighted sum of these two

• Specularities produce a characteristic dogleg in thehistogram of receptor responses– in a patch of diffuse surface, we see a color multiplied by different

scaling constants (surface orientation)– in the specular patch, a new color is added; a “dog-leg” results

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Computer Vision - A Modern ApproachSet: Color

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R

G

B

Illuminant color

Diffuse component

T

S

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Computer Vision - A Modern ApproachSet: Color

Slides by D.A. Forsyth

R

G

B

R

G

B

Diffuseregion

Boundary ofspecularity