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1、Color in Information Display,Maureen StoneStoneSoup Consulting,Effective Color,Illustrators,cartographersArtists,designersA few scientific principles,What is Color?,Physical World,Visual System,Mental Models,Lights,surfaces,objects,Eye,optic nerve,visual cortex,Red,green,brownBright,light,dark,vivid
2、,colorful,dullWarm,cool,bold,blah,attractive,ugly,pleasant,jarring,Perception and Cognition,Color Models,Physical World,Visual System,Mental Models,Physical World,Spectral DistributionVisible lightPower vs.wavelengthAny sourceDirectTransmittedReflectedRefracted,From A Field Guide to Digital Color,A.
3、K.Peters,2003,Cone Response,Encode spectra as three valuesLong,medium and short(LMS)Trichromacy:only LMS is“seen”Different spectra can“look the same”Sort of like a digital camera*,From A Field Guide to Digital Color,A.K.Peters,2003,Effects of Retinal Encoding,All spectra that stimulate the same cone
4、 responseare indistinguishable,Metameric match,Color Measurement,CIE Standard ObserverCIE tristimulus values(XYZ)All spectra that stimulate the same tristimulus(XYZ)response are indistinguishable,From A Field Guide to Digital Color,A.K.Peters,2003,Project X,Y,Z on a plane to separate colorfulness fr
5、om brightness x=X/(X+Y+Z)y=Y/(X+Y+Z)z=Z/(X+Y+Z)1=x+y+z,Chromaticity Diagram,XYZ=xyY,RGB Chromaticity,R,G,B are points(varying lightness)Sum of two colors lies on lineGamut is a triangleWhite/gray/blacknear centerSaturated colorson edges,Display Gamuts,From A Field Guide to Digital Color,A.K.Peters,2
6、003,Projector Gamuts,From A Field Guide to Digital Color,A.K.Peters,2003,Pixels to Intensity,LinearI=kp(I=intensity,p=pixel value,k is a scalar)Best for computationNon-linearI=kp1/Perceptually more uniformMore efficient to encode as pixelsBest for encoding and display,Pixel to Intensity Variation,In
7、tensity Transfer Function(ITF),or“gamma”,Color Models,Physical World,Visual System,Mental Models,TrichromacyMetamerismColor matchingColor measurement,Opponent Color,DefinitionAchromatic axisR-G and Y-B axisSeparate lightness from chroma channelsFirst level encodingLinear combination of LMSBefore opt
8、ic nerveBasis for perceptionDefines“color blindness”,Vischeck,Simulates color vision deficienciesWeb service or Photoshop plug-inRobert Dougherty and Alex W,Deuteranope,Protanope,Tritanope,2D Color Space,Similar Colors,protanope,deuteranope,luminance,Genes in Vischeck,Smart Money,Color Models,Physic
9、al World,Visual System,Mental Models,Separate lightness,chromaColor blindnessImage encoding,Perceptual Color Spaces,Lightness,Hue,Colorfulness,Unique black and whiteUniform differencesPerception&design,Munsell Atlas,Courtesy Gretag-Macbeth,CIELAB and CIELUV,Lightness(L*)plus two color axis(a*,b*)Non
10、-linear function of CIE XYZDefined for computing color differences(reflective),CIELAB,CIELUV,From Principles of Digital Image Synthesis by Andrew Glassner.SF:Morgan Kaufmann Publishers,Fig.2.4&2.5,Page 63&64 1995 by Morgan Kaufmann Publishers.Used with permission.,Psuedo-Perceptual Models,HLS,HSV,HS
11、BNOT perceptual modelsSimple renotation of RGBView along gray axisSee a hue hexagonL or V is grayscale pixel valueCannot predict perceived lightness,L vs.Luminance,L*,Luminance values,L*values,L from HLSAll the same,Corners of the RGB color cube,Lightness Scales,Lightness,brightness,luminance,and L*
12、Lightness is relative,brightness absoluteAbsolute intensity is light powerLuminance is perceived intensityLuminance varies with wavelengthVariation defined by luminous efficiency functionEquivalent to CIE YL*is perceptually uniform lightness,Luminance&Intensity,Intensity Integral of spectral distrib
13、ution(power)Luminance Intensity modulated by wavelength sensitivityIntegral of spectrum luminous efficiency function,Green and blue lights of equal intensityhave different luminance values,Luminance from RGB,L=rLR+gLG+bLBLR,LG,LBMaximum luminance of RGB primariesDifferent for different displays Affe
14、cted by brightness&contrast controlsr,g,bRelative intensity values(linear)Depends on“gamma curve”Not pixel values,Not a fixed equation!,Color Models,Physical World,Visual System,Mental Models,Color differences“Intuitive”color spacesColor scales,Color Appearance,Image courtesy of John MCann,Image cou
15、rtesy of John MCann,Color Appearance,More than a single colorAdjacent colors(background)Viewing environment(surround)Appearance effectsAdaptationSimultaneous contrastSpatial effectsColor in context,Color Appearance ModelsMark Fairchild,surround,background,stimulus,Simultaneous Contrast,Add Opponent
16、ColorDark adds lightRed adds greenBlue adds yellow,These samples will have both light/dark and hue contrast,Affects Lightness Scale,Bezold Effect,Crispening,Perceived difference depends on background,From Fairchild,Color Appearance Models,Spreading,Spatial frequencyThe paint chip problemSmall text,l
17、ines,glyphsImage colorsAdjacent colors blend,Redrawn from Foundations of Vision Brian Wandell,Stanford University,Color Models,Physical World,Visual System,Mental Models,AdaptationContrast effectsImage appearanceComplex matching,Effective Color,What makes color effective?,“Good ideas executed with s
18、uperb craft”E.R.TufteEffective color needs a contextImmediate vs.studiedAnyone vs.specialistCritical vs.contextualCulture and expectationsTime and money,Why Should You Care?,Poorly designed color is confusingCreates visual clutterMisdirects attentionPoor design devalues the informationVisual sophist
19、icationEvolution of document and web design“Attractive things work better”Don Norman,Information Display,Graphical presentation of informationCharts,graphs,diagrams,maps,illustrationsOriginally hand-crafted,staticNow computer-generated,dynamicColor is a key componentColor labels and groupsColor scal
20、es(colormaps)Multi-variate color encodingColor shading and texturesAnd more,www.nps.gov,“Color”includes Gray,Maps courtesy of the National Park Service(www.nps.gov),Color Design,GoalsHighlight,emphasizeCreate regions,groupIllustrate depth,shapeEvoke natureDecorate,make beautifulColor harmony“success
21、ful color combinations,whether these please the eye by using analogous colors,or excite the eye with contrasts.”Principles of Color Design,by Wucius Wong,Color Design Terminology,Hue(color wheel)Red,yellow,blue(primary)Orange,green,purple(secondary)Opposites complement(contrast)Adjacent are analogou
22、sMany different color wheels*See for examplesChroma(saturation)Intensity or purityDistance from grayValue(lightness)Dark to lightApplies to all colors,not just gray,Tints and Tones,Tone or shadeHue+blackDecrease saturationDecrease lightnessTintHue+whiteDecrease saturationIncrease lightness,Gradation
23、s,Color Design Principles,Control value(lightness)Ensure legibilityAvoid unwanted emphasis Use a limited hue paletteControl color“pop out”Define color groupingAvoid clutter from too many competing colorsUse neutral backgroundsControl impact of colorMinimize simultaneous contrast,Envisioning Informat
24、ion,“avoiding catastrophe becomes the first principle in bringing color to information:Above all,do no harm.”E.R.Tufte,Fundamental Uses,To labelTo measureTo represent or to imitate realityTo enliven or decorate,To Label,Identify by Color,Information Visualization Colin Ware,Product Categories,Create
25、d by Tableau-Visual Analysis for DatabasesTM,Grouping,Highlighting,Considerations for Labels,How critical is the color encoding?Unique specification or is it a“hint”?Quick response,or time for inspection?Is there a legend,or need it be memorized?Contextual issuesAre there established semantics?Group
26、ing or ordering relationships?Surrounding shapes and colors?Shape and structural issuesHow big are the objects?How many objects,and could they overlap?Need they be readable,or only visible?,Controls and Alerts,Aircraft cockpit designQuick responseCritical information and conditionsMemorized5-7 uniqu
27、e colors,easily distinguishableHighway signsQuick responseCritical but redundant information10-15 colors?Typical color desktopAid to searchRedundant informationPersonal and decorativeHow many colors?,Psychophysics of Labeling,13579345978274055249379164782541372387659727710386619874367259047362956372
28、836491056763254378795483675456840378465485690,Time proportional to the number of digits,13579345978274055249379164782541372387659727710386619874367259047362956372836491056763254378795483675456840378465785690,Time proportional to the number of 7s,135793459782740552493791647825413723876597277103866198
29、74367259047362956372836491056763254378795483675456840378465785690,Both 3s and 7s“Pop out”,Preattentive,“pop out”,Contrast Creates Pop-out,Hue and lightness,Lightness only,Pop-out vs.Distinguishable,Pop-outTypically,5-6 distinct values simultaneouslyUp to 9 under controlled conditions Distinguishable
30、20 easily for reasonable sized stimuliMore if in a controlled contextUsually need a legend,Radio Spectrum Map(33 colors),http:/www.cybergeography.org/atlas/us_spectrum_map.pdf,Distinguishable on Inspection,Tableau Color Example,Color palettesHow many?Algorithmic?Basic colors(regular and pastel)Exten
31、sible?Customizable?Color appearanceAs a function of sizeAs a function of backgroundRobust and reliable color names,Tableau Colors,Maximum hue separation,Analogous,yet distinct,Sequential,Color Names,Basic names(Berlin&Kay)Linguistic study of namesSimilar namesSimilar evolutionMany different language
32、s,Distinct colors=distinct names?,Distinct,but hard to name,Color Names Research,Selection by nameBerk,Brownston&Kaufman,1982Meier,et.al.2003Image recoloringSaito,et.al.Labels in visualizationDZmura,Cowan(pop out conditions)Healey&Booth(automatic selection)Web experimentMoroney,et.al.2003World Color
33、 Survey(Kay&Cook)http:/www.icsi.berkeley.edu/wcs/,To Measure,Data to Color,Types of data valuesNominal,ordinal,numericQualitative,sequential,divergingTypes of color scalesHue scaleNominal(labels)Cyclic(learned order)Lightness or saturation scalesOrdered scalesLightness best for high frequencyMore=da
34、rker(or more saturated)Most accurate if quantized,Color Scales,Long history in graphics and visualizationWare,Robertson et.alLevkowitz et.alRheingansPRAVDA ColorRogowitz and TreinishIBM ResearchCartographyCynthia Brewer ColorBrewer,Different Scales,Rogowitz&Treinish,“How not to lie with visualizatio
35、n”,Density Map,Lightness scale,Lightness scalewith hue and chroma variation,Hue scale with lightness variation,Phase Diagrams(hue scale),The optical singularities of bianisotropic crystals,by M.V.Berry,Singularities occur where all colors meet,Phases of the Tides,Figure 1.9.Cotidal chart.Tide phases
36、 relative to Greenwich are plotted for all the worlds oceans.Phase progresses from red to orange to yellow to green to blue to purple.The lines converge on anphidromic points,singularities on the earths surface where there is no defined tide.Winfree,1987#1195,p.17.,Brewer Scales,Nominal scalesDistin
37、ct hues,but similar emphasisSequential scaleVary in lightness and saturationVary slightly in hueDiverging scaleComplementary sequential scalesNeutral at“zero”,Thematic Maps,US Census Map,Mapping Census 2000:The Geography of U.S.Diversity,Brewers Categories,Cynthia Brewer,Pennsylvania State Universit
38、y,Color Brewer,www.colorbrewer.org,Tableau Color Example,Color scales for encoding dataDisplayed as charts and graphsQuantized or continuousIssuesColor ramps based on Brewers principlesNot single hue/chroma varying in lightnessCreate a ramp of the“same color”Legible different than distinguishableCen
39、ter,balance of diverging ramps,Heat Map(default ramp),Skewed Data,Slightly negative,Full Range,Skewed Data,Stepped,Skewed Data,Threshold,Skewed Data,Color and Shading,Shape is defined by lightness(shading)“Color”(hue,saturation)labels,Image courtesy of Siemens,CT image(defines shape),PET color highl
40、ights tumor,Color Overlay(Temperature),3D line integral convolution to visualize 3D flow(LIC).Color varies from red to yellow with increasing temperature,http:/www-users.cs.umn.edu/interran/3Dflow.html,Victoria Interrante and Chester Grosch,U.Minnesota,Multivariate Color Sequences,Multi-dimensional
41、Scatter plot,Variable 1,2 X,YVariable 3,4,5 R,G,B,Using Color Dimensions to Display Data Dimensions Beatty and Ware,Do people interpret color blends as sums of variables?,Color Weaves,6 variables=6 hues,which vary in brightness,Additive mixture(blend),Spatial texture(weave),Weaving versus Blending(A
42、PGV06 and SIGGRAPH poster)Haleh Hagh-Shenas,Victoria Interrante,Christopher Healey and Sunghee Kim,Brewer System,http:/www.colorbrewer.org,Brewer Examples,To Represent orImitate Reality,Illustrative Color,Grays Anatomy of the Human Body,Map of Point Reyes,www.nps.gov,ThemeView(original),Courtesy of
43、Pacific Northwest National Laboratories,ThemeScape(commercial),Courtesy of Cartia,To Enliven or Decorate,Visualization of isoelectron density surfaces around moleculesMarc Levoy(1988),Which has more information?Which would you rather look at?,More Tufte Principles,Limit the use of bright colorsSmall
44、 bright areas,dull backgroundsUse the colors found in natureFamiliar,naturally harmoniousUse grayed colors for backgroundsQuiet,versatileCreate color unityRepeat,mingle,interweave,Controlling Value,Get it right in black&white,ValuePerceived lightness/darknessControlling value primary rule for design
45、Value defines shapeNo edge without lightness differenceNo shading without lightness variationValue difference(contrast)Defines legibilityControls attentionCreates layering,Controls Legibility,colorusage.arc.nasa.gov,Legibility,Drop ShadowsDrop Shadow,Drop shadow adds edge,Readability,If you cant use
46、 color wisely,it is best to avoid it entirelyAbove all,do no harm,If you cant use color wisely,it is best to avoid it entirelyAbove all,do no harm.,Why does the logo work?,Value Control,Legibility and Contrast,LegibilityFunction of contrast and spatial frequency“Psychophysics of Reading”Legge,et.al.
47、Legibility standards5:1 contrast for legibility(ISO standard)3:1 minimum legibility10:1 recommended for small textHow do we specify contrast?Ratios of foreground to background luminanceDifferent specifications for different patterns,Contrast and Layering,colorusage.arc.nasa.gov,Value contrast create
48、s layering,What Defines Layering?,Perceptual featuresContrast(especially lightness)Color,shape and textureTask and attentionAttention affects perception Display characteristicsBrightness,contrast,“gamma”,Emergency,Emergency,Emergency,Contrast,General formulationLuminance difference(Lf,Lb)Depends on
49、adaptation and sizeSmall symbols,solid background(Weber)C=(Lf Lb)/LbAdapted to backgroundTextures,high frequency patterns(Michelson)C=(Lf Lb)/(Lf+Lb)Adapted to average,Luminance is intensitymodulated by wavelength sensitivity,Contrast(continued),Contrast using L*1 is ideally visible10 is easily visi
50、ble20 is legible for textReasons to use a light backgroundMore like a reflective surfaceContrast metrics are more accurateEasier to look at in mixed environmentDark background better for dark environments,L*is the same as Munsell Value,computed as a function of L,Grid Example,Grid sits unobtrusively
