The perceptual representation of transparency, lightness, and gloss
OxfordHandbooksOnline
Theperceptualrepresentationoftransparency,lightness,andgloss BartonL.Anderson
OxfordHandbookofPerceptualOrganization
EditedbyJohanWagemans
PrintPublicationDate: Jul2015
OnlinePublicationDate: Aug
2014
Subject: Psychology,Neuropsychology
DOI: 10.1093/oxfordhb/9780199686858.013.030
AbstractandKeywords
Thestructureinlightiscreatedbyitsinteractionwithsurfacesandmaterialsthatfillourenvironment.We
experienceourenvironmentasa3Dlayoutofsurfacesandmaterialsthatpossessqualitiessuchascolor,
lightness,opacity,gloss,andshape.Oneofthemostfundamentalproblemsinvisionscienceinvolves
understandinghowthevisualsystemseparatesthesedifferentsourcesofimagestructureandgeneratesour
experienceofthesedifferentsurfacesandmaterialattributes.Inthischapter,Idiscussthetheoreticalissuesthat
ariseinattemptstocraftsolutionstotheseproblems,anddescribeabodyofempiricaldatathatbearsonthe
relationshipbetweenthedimensionsofperceptualexperienceandthephysicalsourcesofvariabilitygeneratedby
theworld.
Keywords:light,color,lightness,opacity,gloss,shape,visionscience,structure,dimension,perception
1.Theoreticalpreliminaries
Theadaptiveroleofvisionistoprovideinformationaboutthebehaviorallyrelevantpropertiesofourvisual
environment.Ourevolutionarysuccessreliesonrecoveringsufficientinformationabouttheworldtofulfillour
biologicalandreproductiveneedswhileavoidingenvironmentaldangers.Theattempttounderstandvisionasa
collectionofadaptationstospecificcomputationalproblemshasshapedagrowingbodyofresearchthattreats
visionasadecomposablecollectionof‘recovery’problems.Inthisview,perceptualoutputsareunderstoodas
approximatelyidealsolutionstospecificrecoveryproblems,whichhavebeendubbedthe‘naturaltasks’ofvision
(GeislerandRingach2009).Fromthisperspective,thescienceofunderstandingvisualprocessingproceedsby
identifyinganorganism’snaturaltasks,evaluatingtheinformationavailabletoperformeachtask,developing
modelsofhowtoperformataskoptimally,anddiscoveringthemechanismsthatimplementthesesolutions.
Thefirstaspectofthismethodofapproach—theidentificationof‘naturaltasks’—isarguablythemostimportant
becauseitdefinestheproblemthatneedstobesolved.Itisalsotheleastconstrained.Anyenvironmentalproperty
canbehypothesizedtobesomethingthatcouldhaveadaptivevalueandthereforesomethingthatmightprovidea
selectiveadvantagetoanyoneequippedtorecoverit.Presumably,however,onlysomeaspectsofour
environmentwereinvolvedindirectlyshapingtheevolutionofoursenses.Thescientificchallengeisto
differentiatepropertiesthatactuallyexertedselectivepressureinshapingthedesignofoursensesfromthosethat
merelycamealongforthe‘evolutionaryride’(perceptual‘spandrels’).Butthereiscurrentlynoprincipledmeansof
makingsuchdistinctions.Forexample,ageneralargumentcouldbe(andhasbeen)madethatthecomputationof
surfacelightnesswouldbeusefulbecauseitprovidesinformationaboutanintrinsicpropertyoftheexternalworld,
butitismuchhardertofashionaclearargumentabouthowtherecoveryofsurfacealbedoprovidesaspecific
adaptivebenefit,orthatanysuchbenefitplayedaroleinnaturalselection.
Thesecondaspectoftheadaptationistapproach—identifyingtheinformationavailableforacomputation—isin
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The perceptual representation of transparency, lightness, and gloss
principlemoreconstrained.Naturalscenesarerepletewithinformationthatcouldbeusedtosenseaparticular
worldproperty.Oncearecoveryproblemhasbeenidentified,itispossibletoinventorythesourcesofinformation
thatexistinthenaturalworldthatcanbeusedtosenseit.However,mostrecoveryproblemsinvision(suchas
shape,depth,color,lightness,etc.)areconsideredinisolation,oftenininformationallyimpoverishedlaboratory
settings.Thisapproachhasledtothenearlyuniversalacceptanceofabeliefinthepovertyofthestimulus:the
presumptionthattheimagesdonotcontainsufficientinformationtorecovertheaspectsoftheworldthatwe
experience.Thisviewistypicallydefendedbydemonstratingthatitisimpossibletoderiveauniquesolutionfora
specificrecoveryproblembasedontheinformationavailableintheimages.Perceptionisconstruedastheoutputs
ofacollectionofunder-constrainedproblemsofprobabilisticinference,whicharesolvedwiththeaidofadditional
information,assumptions,orconstraints.Soconstrued,itisnaturaltoturntoprobabilitytheoryforguidanceinto
howtosolvesuchinferenceproblemsideally,whichtypicallyentailstheapplicationofBayes’theorem(see
Feldman’schapter,thisvolume).
Thethirdaspectoftheadaptationistprogramisostensiblytheeasiest,andiswheretheorymeetsdata.Perceptsor
perceptualperformanceofobserversiscomparedtothatoftheBayesianideal,constructedonasetofpriorsand
likelihoods.WhendataandtheBayesianidealaredeemedsufficientlysimilar,theexplanatorycircleisconsidered
closed:thefitbetweenmodelanddataisupheldasevidentialsupportforthespecificationofthenaturaltasks,the
selectionofpriorsandlikelihoodsneededtoperformtheinference,andtheclaimthatperceptioninstantiatesa
formofBayesianinference.Allthatremainsisthediscoveryofthemechanismsthatinstantiatesuchcomputations.
Theprecedingdescribeswhatmaycurrentlybeconsideredone(ifnotthe)dominantviewonhowtoapproachthe
studyandmodelingofvisualprocesses.Myownviewdepartsinanumberofsignificantwaysfromthisapproach,
whichshapesbothmyselectionofproblemsandthetheoreticalapproachtakentoaccountfordata.Oneofthe
maingoalsofthischapteristoprovideanoverviewofhowmyapproachhasshapedworkinthreeareasof
surfaceandmaterialperception:transparency,lightness,andgloss.Thegistofmyapproachmaybearticulated
asfollows.First,Iassumethattheattempttoidentifythe‘naturaltasks’ofvision—i.e.,thecomputational‘problems’
thatvisualsystemsputativelyevolvedtosolve—isatbestaguessinggame,andatworstatheoreticalfiction.
Someofthe‘problems’ourvisualsystemsseemtosolvemaybeepiphenomenaloutputs,notexplicitadaptations.
Second,theclaimthatvisionisanill-posedinferenceproblemisalogicalconsequenceoftreatingvisionasa
collectionofrecoveryproblems,forwhichitcanbeshownthatthereisnoclosedformsolutionthatcanbederived
fromtheinformationthatiscurrentlyavailable.Butiftheputative‘recoveryproblem’ismisidentified,orthe
‘informationavailableforsolvingit’isartificiallyrestricted(suchastypicallyoccursinlaboratoryenvironments),
thenitmaynotbevisionthatisill-posed,butourparticularunderstandingofvisualprocessingthatis
misconstrued.
Analternativeapproachistobeginwithwhatwevisuallyexperienceabouttheworld,andattempttodetermine
whatimagepropertiesmodulatetheseexperiences.Thequestionisnotwhetherthereissufficientinformationin
theimagestospecifythetruestatesoftheworld,butrather,whetherthereissufficientinformationtoexplainwhat
weexperienceabouttheworld.Thisapproachisneutralastothe‘computationalgoals’ofthevisualsystem,orif
evenwhethertheideaofacomputationalgoalhasanyrealmeaningforbiologicalsystems.Whereastherecovery
ofaworldpropertycanbeshowntobeunder-constrainedbyargument,thequestionwhetherthereissufficient
informationavailabletoexplainwhatweexperienceabouttheworldisanempiricalquestion.
2.Disentanglingimagesintocausalsources
Weexperiencetheworldasacollectionof3Dobjects,surfaces,andmaterialsthatpossessavarietyofdifferent
phenomenologicalqualities.Thereflectanceandtransmittancepropertiesofamaterial,togetherwithits3D
geometry,structurelightinwaysthatmodulatesourexperienceofshape,lightness,color,gloss,texture,and
translucency.Someimagestructurealsoarisesfromtheidiosyncraticdistributionoflightsourcesinascene—the
illuminationfield.Toafirstapproximation,thislistofsurfaceandmaterialpropertiestendtobeexperiencedas
separatesourcesofimagestructure,despitethefactthattheyareconflatedintheimage.Muchresearchinto
perceptualorganizationhasfocusedonhowthevisualsystemfillsinmissinginformationorgroupsimage
fragmentsintoaglobalstructureorpattern.Whilesuchphenomenaareanextremelyimportantaspectofour
visualexperience,oneoftheotherfundamentalorganizationalproblemsinvolvesunderstandinghowthevisual
systemdisentanglesdifferentsourcesofimagestructureintothedistinctsurfaceandmaterialqualitiesthatwe
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The perceptual representation of transparency, lightness, and gloss
experience.Inwhatfollows,Iconsideravarietyofsegmentationproblemsintheperceptionofsurfaceandmaterial
attributes,andtheinsightsthatsuchproblemsshedonthebroadertheoreticalissuesraisedabove.
2.1.Transparency
Oneoftheperceptuallymostexplicitandtheoreticallychallengingformsofimagesegmentationoccursinthe
perceptionoftransparency.Historically,thestudyoftransparencyfocusedonachromaticsurfaces,whichwas
largelyduetheseminalinfluenceofMetelli’smodeloftransparency(Metelli1970,1974a,1974b,1985;seealso
Gerbino’schapter,thisvolume).Theperceptionof(achromatic)transparentsurfacesgeneratestwodistinct
impressions:itsperceivedlightnessanditsperceivedopacityor‘hidingpower’.Metelli’smodelwasbasedona
simplephysicaldeviceknownasanepiscotister:arapidlyrotatingdiscwithamissingsector.Theproportionof
thediskthatis‘missing’determinestheamountoflighttransmittedfromtheunderlyingsurfacesthroughthe
episcotisterblades,whichisthephysicalcorrelateofatransparentsurface’stransmittance.Thelightness(or
albedo)ofthetransparentsurfacecorrespondedtothecolorofthepaintusedonthefrontsurfaceofthe
episcotister,whichdeterminesthecolorofthetransparentlayer(orforachromaticpaints,itslightness).Metelli’s
modelwasrestrictedto‘balanced’transparency,whichreferredtoconditionswheretheepiscotisterhadauniform
reflectanceandtransmittance,reducingeachtoasinglescalar(number).ForthesimplebipartitefieldsMetelliused
asbackgrounds,thisallowedequationsforthetotalreflectedlightintheregionsofoverlaytobewrittenasasum
oftwocomponents:amultiplicativetransmittanceterm,whichdeterminedtheweightforthecontributionofthe
underlyingsurface;andanadditiveterm,whichcorrespondsthelightreflectedbytheepiscotistersurface.By
construction,Metelliconsidereddisplayscontainingtwouniformlycoloredbackgroundregions,whichgavehima
systemoftwoequationsandtwounknownsthatcouldbesolvedinclosedform.Asignificantbodyofworkshowed
thattheperceptionoftransparencyisoftenwellpredictedbyMetelli’sepiscotistermodel:balancedtransparency
isperceivedwhendisplayswereconsistentwiththeepiscotisterequations,butgenerallynototherwise.Notethat
Metelli’smodelserveddoubledutyasbothaphysicalmodeloftransparencyandapsychologicalmodelofthe
conditionsthatelicitperceptsoftransparency.
Despitethesesuccesses,Metellihimselfnotedacuriousdiscrepancybetweenthepredictionsoftheepiscotister
modelandperception:alightepiscotisterlookslesstransmissivethandarkepiscotister(Metelli1974a).Froma
‘recovery’pointofview,thisconstitutesaperceptualerror,andhencenon-idealperformance,butalmostno
experimentalworkwasconductedtounderstandthisdeviationfromthepredictionsofMetelli’smodel.Wetherefore
performedaseriesofexperimentstotestwhetherthephysicalindependenceofopacityandlightnessisobserved
psychophysically(SinghandAnderson2002).Observersmatchedthetransmittanceofsimulatedsurfacesthat
variedinlightness,andthelightnessoftransparentfiltersthatvariedintransmittance.Wefoundthatlightness
judgmentsweremodulatedbysimulatedtransmittance,andtransmittancejudgmentsweremodulatedbysimulated
variationsinlightness.Thus,althoughthetransmittanceandreflectanceoftransparentlayersarephysically
independentparametersinMetelli’smodel,theyarenotexperiencedasbeingindependentperceptually.
Whattheoreticalconclusionscanbedrawnfromtheseresults?Metelli’smodeltreatedaphysicalmodelof
transparencyasaperceptualmodeloftransparency.Ourfindingsofmutual‘contamination’ofthetransmittance
andlightnessofthetransparentfilterimpliesoneoftwopossibilities:(1)thereisnosimplecorrespondence
betweenthedimensionsofaphysicalmodelandaperceptualmodel,or(2)thatMetelli’smodelisthewrong
physicalmodelonwhichtobasetheoriesofperceivedtransparency.Withrespectto(1),Metelli’smodelequates
theperceivedopacityofanepiscotisterwithitsphysicaltransmittance,andhencecannotexplainwhylight
episcotisterslookmoreopaquethandarkepiscotisters.Thedependenceofperceivedopacityonlightnesscanbe
readilyunderstood,however,ifthevisualsystemreliedonimagecontrasttoassessthehidingpowerof
transparentsurfaces.Alightepiscotisterreducesthecontrastofunderlyingsurfacestructuremorethanan
otherwiseidenticaldarkepiscotister,andhence,shouldappearmoreopaqueifthevisualsystemusesimage
contrasttoassessperceivedopacity1.Indeed,itseemsalmostinevitablethatthevisualsystemutilizescontrastto
judgetheperceivedopacityoftransparentfilters,sincecontrastdeterminesthevisibilityofimagestructurein
general.Butthisimpliesthatthevisualsystemisusingthe‘wrong’imagepropertiestogenerateourexperienceof
aworldproperty,andhencewillalmostalwaysresultinthe‘wrong’answer.Fromtheperspectiveofexplainingour
experience,suchissuesarelargelyirrelevant;theonlyissueiswhetherthereissufficientinformationintheimage
toexplainwhatitisweexperienceabouttheworld,notwhethersuchperceptsareveridical.
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The perceptual representation of transparency, lightness, and gloss
Alternatively,itcouldbe(andhasbeen)arguedthatthediscrepancybetweenperceptionandMetelli’smodel
merelyprovidesevidencethatthereissomethingwrongwithMetelli’smodel,anddoesnotimpactonthemore
generalclaimthatperceptioncanbeidentifiedwiththerecoveryofsomephysicalmodel.FaulandEkroll(2011)
havemadepreciselythisargument.Theycontendthatasubtractivefiltermodelbettercapturestheperceptionof
chromatictransparency,andhencemaybeamoreappropriatemodelofachromatictransparencyaswell.
Althoughthereiscurrentlyinsufficientdatatodeterminewhichofthesealternativesisultimatelycorrectfor
achromaticstimuli,FaulandEkrollreportedsubstantialdiscrepanciesbetweentheirfiltermodelandperceived
transparencywhenthechromaticcontentoftheilluminantwasvaried,despitedemonstratingthattherewas
theoreticallysufficientinformationforamuchbetterlevelofperformance(FaulandEkroll2012).Atthisjuncture,
thereiscurrentlynophysicalmodelthatmapsdirectlyontoourexperienceoftransparentsurfaces,anditis
largelyamatterofscientificfaiththatsuchamodelmayultimatelybediscovered.
2.2.Lightness
Theperceptionoflightnessalsohasbeentreatedasakindofsegmentationproblem.Forachromaticsurfaces,the
termlightness(oralbedo)referstoasurface’sdiffusereflectance.Thelightreturnedtotheeyeisaconflated
mixtureoftheilluminant,surfacereflectance,and3Dpose.Thereiscurrentlyextensivedebateoverthe
computations,mechanisms,and/orassumptionsthatareresponsibleforgeneratingourexperienceoflightness
(seeGilchrist’schapter,thisvolume).Therearefourgeneraltheoreticalapproachestotheproblemoflightness:
scission(orlayersmodels),equivalentilluminantmodels,anchoringmodels,andfilterorfilling-inmodels.Iconsider
eachmodelclassinturn.
2.2.1.Modelsandtheoriesoflightness
Scissionmodels
Scissionmodelsassertthatthevisualsystemderiveslightnessbyexplicitlysegmentingtheilluminantfromsurface
reflectanceinamanneranalogoustothedecompositionthatoccursinconditionsoftransparency.Suchmodels
havebeendubbedlayers,scission,orintrinsicimagemodels(Adelson1999;Anderson1997;Andersonand
Winawer,2005,2008;Barrowetal.1978;Gilchrist1979).Inmodelsoflightness,scissionmodelsassertthatthe
visualsystemteasesapartthecontributionsofreflectance,theilluminant,and3Dpose.Althoughsomeauthors
associatescission(orintrinsicimage)modelswithveridicalperception(Gilchristetal.1999),thereisnothing
inherentinscissionmodelsthatmandatesthisassociation.Theconceptofscissionentailsaclaimabouta
particularrepresentationalformatorprocessofimagedecompositionthatispresumedtounderlieourexperience
oflightness.Thehypothesizedsegmentationprocessesresponsibleforgeneratingtheputativelayered
representationmayormaynotresultinveridicallightnessperceptsdependingonhow(andhowwell)thevisual
systemperformsthehypothesizeddecomposition.
Equivalentillumination
Onemodelthatisconceptuallyrelatedtolayersmodelsistheequivalentilluminationmodel(EIM)developedby
BrainardandMaloney(2011).Aswithlayersmodels,theEIMassumesthatthevisualsystemrecoverssurface
reflectancebyfactoringtheimageintotwocomponents:anestimateoftheilluminant(whichtheyterman
‘equivalentilluminant’)andsurfacereflectance.Whereaslayersmodelshaveassumedthatthereisanexplicit
representationofboththeilluminantandsurfacereflectance,thesameisnotnecessarilytruefortheEIM.TheEIM
isatwo-stagemodelwhichassertsthatthevisualsystembeginsbygeneratinganestimateoftheilluminant,and
usesthisinformationinasecondstagetoderivesurfacereflectancepropertiesfromtheimagedata.Thismodel
remainsmuteastohowthevisualsystemestimatestheparametersoftheestimatedilluminantfromimagesand
alsoremainsuncommittedastotheanyrepresentationalformattheEImaytake.Themainexperimentally
assessableclaimisthatitpredictsthattheparametricstructureofcolororlightnessmatchescanbedescribedby
someEIM.TheapproachoftheEIMcanbeunderstoodasfollows:Givenasetofreflectancematches,isitpossible
tofindamodeloftheilluminantthatisconsistentwiththematches?Notethatthereisnopresumptionthatthe
particularEIMthatputativelyshapesobserver’smatchesisveridical;theonlyclaimisthatobservers’lightness
matchesareshapedbysomeEIM.Indeed,thebenefitofthisclassofmodelisthatitcaninprincipleaccountfor
bothveridicalmatchesand/orthespecificpatternoffailuresinveridicality.
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The perceptual representation of transparency, lightness, and gloss
Anchoringtheory
Athirdtheoreticalapproachtolightnessiscapturedbyanchoringtheory,whichwasdevelopedinanattemptto
accountforavarietyofsystematicerrorsintheperceptionoflightness(Gilchristetal.1999).UnlikelayersorEIM
models,thereisnoexplicitfactorizationoftheilluminantandreflectanceinanchoringtheory.Rather,anchoring
theoryassertsthatperceivedlightnessisderivedthroughasetofheuristicrulesthatthevisualsystemusesto
mapluminanceontoperceivedlightness.Therearetwomaincomponentstoanchoringtheory(seeGilchrist’s
chapter,thisvolume).First,followingWallach(1948),luminanceratiosareusedtoderiveinformationaboutrelative
lightness.Whenthefull30:1rangeofphysicallyrealizablereflectancesarepresentinacommonilluminant,the
truereflectanceofsurfacescanbederivedonthebasisoftheseratiosalone.However,inscenescontainingless
thanthisfull30:1range,someadditionalinformationorruleisneededtotransformambiguousinformationabout
relativelightnessintoanestimateofabsolutesurfacereflectance.Forexample,animagecontaininga2:1rangeof
luminancescouldbegeneratedbysurfaceswithreflectancesofthreepercentandsixpercent,orfivepercent
and10percent,40percent,80,adinfinitum.Anchoringtheoryassertsthatthisambiguitymustberesolvedwith
ananchoringrule,suchthataspecificrelativeimageluminance(suchasthehighest)ismappedontoafixed
lightnessvalue(suchaswhite).Allotherlightnessvaluesinasceneareputativelyderivedbycomputingratios
relativetothisanchorvalue.Anumberoffixedpointsarepossible(e.g.,theaverageluminancecouldbegrey,the
highestluminancecouldbewhite,orthelowestluminancecouldbeblack),butavarietyofexperiments,especially
thosefromGilchrist’slab,havesuggestedthatinmanycontexts,thehighestluminanceisperceivedaswhite.
Filteringandfilling-inmodels
Athirdapproachtolightnesstreatlightnessperceptsastheoutputsoflocalimagefiltersapplieddirectlytothe
images(BlakesleeandMcCourt2004;DakinandBex2003;KingdomandMoulden1988,1992;ShapiroandLu
2011).Suchapproachestypicallydonotdistinguishbetweenperceivedlightness(perceivedsurfacereflectance)
andbrightness(perceivedluminance),atleastnotexplicitlyintheconstructionofthemodel.Rather,anewimage
isgeneratedfromasetoftransformationsappliedtotheinputimage.Inastrictsense,filtermodelsarenottruly
lightnessmodels,sincetheysimplytransformoneimageintoanotherimage.Suchmodelsaremoreappropriately
construedasmodelsofbrightnessthanlightness,sincethereisnoexplicitattempttorepresentsurface
reflectance,ordistinguishreflectancefromluminance.Theirrelevancetounderstandinglightnessdependsonthe
extenttowhichthedistinctionbetweenbrightnessandlightnessmakesbiologicalorpsychologicalsensefora
givenimageorexperimentalprocedure.Likeanchoringmodels,filterapproachestolightnessdonotexplicitly
segmentimageluminanceintoseparatecomponentsofreflectanceandillumination.
Inarelatedmanner,avarietyoffilling-inmodelshavebeenproposedthatdonotexplicitlydistinguishlightness
andbrightness(GrossbergandMingolla1985;ParadisoandNakayama1991;RuddandArrington2001).Such
modelsinvokeatwostageprocess:onethatrespondstothemagnitudeandorientationof‘edges’(oriented
contrast)and/orgradients,andasecondprocessthatpropagatesinformationbetweensuchlocalized‘edge’
responsestogenerateafully‘filled-in’orinterpolatedperceptofbrightnessorcolor.
2.2.2.Evaluatingtheoriesoflightness
Asnotedinarecentarticle,thetopicoflightnessandbrightnesshashistoricallybeenquitedivisive(Kingdom
2011).Onesourceofdisagreementinvolvestheverydistinctionbetweenbrightnessandlightness.Althoughsuch
constructsareeasilydistinguishedfromeachotherwithregardtotheirintendedphysicalreferents,itisnotclear
that(orwhen)suchdistinctionshavepsychologicalmeaning.Thedistinctionbetweenlightnessandbrightnessis
particularlyproblematicforthekindsofdisplaysthataretypicallystudiedineitherlightnessorbrightnessstudies.
Inalmostallcases,thetargetsofinteresthaveasingle,uniformluminance(orapproximatelyso),andare
embeddedinhighlysimplifiedgeometricandilluminationcontexts.Forscenesdepictingrealorsimulatedsurfaces,
thesurfacesofinterestaretypicallyflat,matte,andarrangedinasingledepthand/orilluminant.Theytypically
lackinformationaboutthelightfield,suchasthatprovidedbyspecularreflections,3Dstructure,shading,and
inter-reflections.Itisperhapsnotsurprising,then,thatthefieldremainsdividedastotheproperwaytounderstand
howsuchimpoverisheddisplaysareexperienced,sinceitisunclearwhetherthedistinctionbetweenlightnessand
brightnessispsychologicallymeaningfulinmanyofthesedisplays.Inwhatfollows,Iwillconsidersomerecent
evidencerelevantforeachofthetheoriesoflightnessdescribedabove.
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The perceptual representation of transparency, lightness, and gloss
Clicktoviewlarger
Figure1 .StereoscopicKanizsafiguredemonstratingtheroleofscissiononperceivedlightnessfortwo
differentgreyvalues.Thesmallpieshapedinducingsectorsarethesameshadeofdarkgreyinthetoptwo
rows,andthesameshadeoflightgreyinthebottomtworows.Whenthelefttwoimagesarecrossfused,
ortherighttwoimagesdivergentlyfused,anillusorydiamondisexperience.Notethatthediamondsinthe
firstandthirdrowsappearmuchlighterthantheircorrespondingfiguresinthesecondandfourthrows.
AdaptedfromAnderson(1998,TrendsinCognitiveScience).
Thecoreclaimofscissionmodelsisthatourexperienceoflightnessinvolvesthedecompositionoftheinputinto
separablecauses.Oneofthedifficultiesinassessingscissionmodelsisthatitisnotalwaysclearwhether(or
when)suchseparationoccurs,orwhatcriteriathatshouldbeappliedtodeterminewhethersuchdecomposition
occurs.Onecanbeginbyposingaquestionofsufficiency:Canscissioninducetransformationsinperceived
lightnesswhenitisphenomenallyapparent?Themostphenomenologicallycompellingsenseofscissionoccursin
conditionsoftransparency,whichrequiresthesatisfactionofbothgeometricandphotometricconditions.One
techniqueforinducingscissioninvolvesmanipulatingtherelativedepthandphotometricrelationshipsof
stereoscopicKanizsafiguressuchasthosedepictedinFigure1.Whenthegrey,wedge-shapedsegmentsofthe
Kanizsafigure’sinducingelementsinFigure1aredecomposedintoatransparentlayeroverlyingawhitedisk
(secondandfourthrowsofFigure1),theyappearsubstantiallydarkerthanwhenthesamegreysegmentappears
tooverlieadarkdisk(firstandthirdrowsofFigure1).Notethatthecoloroftheunderlyingcircularinducing
elementappearstobe‘removed’fromthegreywedge-shapedsegmentsandattributedtothemoredistantlayer,
whichputativelytransformstheperceivedlightnessofthetransparentlayer.Notealsothatthedirectionofthe
lightnesstransformationdependsonwhichlayerobserversareaskedtoreport.Ifobserversareaskedtoreport
thecolorofthefarlayerunderneaththegreysectorsofthetopimage,theyreportitasappearingquitedark
(nearlyblack),sincethisisthecoloroftheinterpolateddisc.Butiftheyareaskedtoreportthenearlayerofthe
transparentregion,theyreportitasappearingquitelight.
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The perceptual representation of transparency, lightness, and gloss
Clicktoviewlarger
Figure2 .Stereoscopicnoisepatternscanalsobedecomposedintolayersinwaysthatinducelarge
transformationsinperceivedlightness.Ifthelefttwoimagesarecrossfusedortherighttwoimages
divergentlyfused,thetopimageappearstosplitintoapatternofdarkcloudsoverlyinglightdiscs(top),or
lightcloudsoverlyingdarkdisks(bottom).Thetexturesinthetopandbottomarephysicallyidentical.
AdaptedfromAnderson(1999).
Clicktoviewlarger
Figure3 .Scissioncanalsobeinducedbyaselectivegroupingthelightanddarkcomponentsoftextureof
thetargets(chesspieces)withthesurround.Thetextureswithinthechesspiecesinthetopandbottom
imagesareidentical,butappearasdarkcloudoverlyinglightchesspiecesonthetop,andlightclouds
overlyingdarkchesspiecesonthebottom.
AdaptedfromAndersonandWinawer(2005).
Inordertoprovidemoreconclusiveevidencefortheeffectsofscissiononperceivedlightness,Iconstructed
stereoscopicvariantsofFigure1usingrandomnoisetextures.Thegoalwastoinducetransparencyinatexture
suchthatthelightanddark‘components’ofthetexturewouldperceptuallysegregateintodifferentdepthplanes.
AnexampleispresentedinFigure2.Whenthelefttwocolumnsarecross-fused,vividperceptsofinhomogeneous
transparencycanbeobserved:Thetopimageappearsasdarkcloudsoverlyinglightdisks,andthebottom
appearsaslightcloudsoverlyingdarkdisks.Notethatthelightestcomponentsofthetextureinthetopimage
appearasportionsoftheunderlyingdiscinplainview,whereasthesameregionsinthebottomimageappearas
themostopaqueregionsofthelightcloudsinthebottomimage(andviceversaforthedarkregions).We
subsequentlyshowedthatsimilarphenomenacouldbeobservedinnon-stereoscopicdisplays.Intheseimages,
scissionwasinducedbyembeddingtargetsinsurroundsthatcontaintexturesthatselectivelygroupwitheitherthe
lightordark‘components’ofthetextureswithinthetargets(Figure3).Aswiththeirstereoscopicanalogues,the
whiteandblackchesspiecesareactuallyphysicallyidentical(i.e.,containidenticalpatternsoftexture).Notethat
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The perceptual representation of transparency, lightness, and gloss
theluminancevariationswithinthetextureofthechesspiecefiguresareexperiencedasvariationsintheopacity
ofatransparentlayerthatoverlieauniformlycoloredsurface.Theopacityofthetransparentsurfaceisgreatest
forluminancevaluesthatmostcloselymatchthesurroundalongthebordersofthechesspieces(darkontop,light
onthebottom),andtheleastopaquewhenforluminancevaluesthataremostdifferentfromthesurround(lighton
top,darkonthebottom).Notethatthelightestregionswithinthetargetsonthedarksurroundappearinplainview,
andthedarkestregionswithinthetargetsappearinplainviewonthelightsurround.Thisbiasisevidentfor
essentiallyallrangesoftargetluminancetested,althoughthisperceptualfactisinnowaymandatedbythe
physicsoftransparency,particularlyforunderlyingsurfacesthatdonotappearblackorwhite.
Thesephenomenademonstratethatscissioncaninducestrikingtransformationsinperceivedlightnessin
conditionsoftransparency,butitdoesnotaddressthebroaderquestionofwhetherscissionplaysarolein
generatingourexperienceoflightnessinconditionsthatdonotgenerateexplicitperceptsofmultiplelayersor
transparency.
EIMsalsoassertthattheperceptionofsurfacecolorandlightnessisderivedbydecomposingtheimageinto
estimatesoftheilluminantandsurfacereflectance.Theevidenceinsupportofthismodelis,however,
phenomenologicallyindirect.WorkfromBrainard’sandMaloney’slabshavedemonstratedthattheparametric
structureofavarietyofmatchingdatacanbeexplainedwithatwo-stagemodelinwhichthefirststageinvolvesan
estimationoftheilluminant(an‘equivalentilluminant’),whichisthenusedtoderiveobservers’reflectancematches
fromtheinputimages(BrainardandMaloney,2011).
UnlikescissionmodelsorEIMs,anchoringtheoryassertsthatlightnessisderivedwithoutexplicitlydecomposing
theimagesintoanexplicitrepresentationofilluminationandreflectance.Thecentralpremiseofanchoringtheory
isthatthevisualsystemsolvestheambiguityoflightnessbytreatingaparticularrelativeluminanceasafixed
(anchor)pointonthelightnessscale(namely,thatthehighestluminanceaswhite),independentofthelevelof
illuminationorabsoluteluminancevaluesinascene.Totestthisclaim,weconstructedbothpaperMondrians
displayedinanotherwiseuniformlyblacklaboratory,andsimulatedMondriansdisplayedonaCRTinadarkblack
labroom(Andersonetal.2008).Inallcases,thehighestluminanceintheroomwasthecentraltargetpatchofthe
Mondriandisplay.Wevariedboththereflectancerangeandilluminationleveloftheformer(i.e.,paperMondrians),
andthesimulatedreflectancerangeandsimulatedilluminantlevelsofthelattersimulatedMondrians.Forrestricted
reflectanceranges(3:1orless),wefoundthatthehighestluminancecouldvaryinperceivedlightnessasa
functionofillumination.ForoursimulatedilluminantsandMondriandisplays,observers’lightnessmatches
(expressedasapercentageofreflectance)werealogarithmicfunctionof(simulated)illuminant,ratherthanan
invariant‘white’aspredictedbyanchoringtheory.Theseresultssuggestthattheapparent‘anchoring’of
luminanceto‘white’isaconsequenceoftheparticularexperimentalconditionsthathavebeenusedtoassessthis
model,ratherthanreflectinganinvariant‘anchorpoint’usedtoscaleotherlightnessvalues.
Somerecentdatahasprovidedsomestrongevidenceagainstanexplicitilluminationestimationmodel,andmore
generally,anymostthatreliesonluminanceratiostocomputeperceivedlightness(suchasanchoringtheory).
Radonjicetal.(2011)conductedexperimentsdepictingcheckerboarddisplaysinadisplaycapableofdisplaying
anextremelylargedynamicrange,andfoundthatobserversmappedaveryhighdynamicrange(~10,000:1)onto
anextendedlightnessrangeof100:1,whichspannedfrom‘white’to‘darkblack’(thedarkestvalueswere
obtainedusingglossypapers).Suchbehaviorwouldnotbeexpectedforanymodelthatattemptstoinfera
physicallyrealizableilluminant,oranyrealizablereflectanceratiosofrealsurfaces,asembracedbyanchoring
theoryortheEIM.
OnecommonassumptionofanchoringtheoryandtheEIMisthatthevisualsystemexplicitlyattemptstoextractan
estimateoflightnessthatcorrespondstothephysicaldimensionofsurfacealbedo.TheresultsofRadonjićetal.
(2011)providecompellingevidenceagainstthisview.Justasourexperienceoftransparencymaynothaveany
directcorrespondencetothephysicaldimensionsthatmodulateperceivedtransparency(suchastransmittance),
theperceptionoflightnessmaynotrepresentanapproximationofthephysicaldimensionofsurfacealbedo.The
resultsofRadonjicetal.provideevidencethatdirectlychallengeanyattempttointerpretthevisualresponseasa
‘bestguess’astotheenvironmentalsourcesthatproducedtheirstimuli,sincethereisnocombinationofsurface
reflectanceandilluminantthatcanproducesuchstimuli(atleastinacommonilluminant).Iwillreturntothis
generalpointinthegeneraldiscussionbelow.
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The perceptual representation of transparency, lightness, and gloss
3.Gloss
Theexperienceofglossisanotheraspectofourexperienceofsurfacereflectancethathasreceivedagrowing
amountofexperimentalattention.Whereastheconceptofsurfacelightnesshasbeencastastheproblemof
understandinghowweexperiencethediffusereflectanceofasurface,theperceptionofglossistypicallycastas
theproblemofunderstandinghowweexperiencethespecular‘component’ofreflectance.Fromagenerativepoint
ofview,thediffuseandspecular‘components’ofreflectancearetreatedascomputationallyseparable.So
construed,theproblemofglossperceptioninvolvesunderstandinghowthevisualsystemsegmentstheimage
structuregeneratedbyspecularreflectancefromdiffusereflectance(andallothersourcesofimagestructure).
Theapparentintractabilityofthisproblemhasinspiredattemptstofindcomputationalshort-cutstoavoidthe
complexityofthisdecompositionproblem.Oneapproachassertsthatthevisualsystemusessimpleimage
statisticsthatdonotrequireanyexplicitdecompositionoftheimagesintodistinctcomponentsofreflectanceto
deriveourexperienceofgloss.Motoyoshietal.(2007)arguedthatperceivedglosswaswellpredictedbyan
image’shistogramorsub-bandskew,ameasureoftheasymmetryofthepixelhistogram(orresponseofcentersurroundfilters)respectively.Thisclaimwasevaluatedforaclassofstuccosurfaceswithastatisticallyfixedlevel
ofsurfacereliefthatwereviewedinfixedilluminationfield.Intheseconditions,glossysurfacesgeneratedimages
withastrongpositiveskew,whereasmattesurfacesgeneratedsurfaceswithnegativeskew.Theattractivefeature
ofthiskindofmodelisthatitpotentiallyreducesacomplexmid-levelvisionproblemintoacomparativelysimple
problemofdetectinglow-levelimageproperties.
Clicktoviewlarger
Clicktoviewlarger
Figure4 .Theperceptionofglossdependscriticallyhighlightsappearinginthe‘rightplaces’ofasurface’s
diffuseshadingprofile.InA,thehighlightsappearneartheluminancemaximaofthediffusedshading
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The perceptual representation of transparency, lightness, and gloss
profileandhavesimilarorientations,andthesurfaceappearsrelativelyglossy.InB,thehighlightshave
beenrotatedsothattheyappearwithrandompositionsandorientationsrelativetothediffuseshading
profile,anddonotappearglossy.
AdaptedfromAndersonandKim(2009).
However,subsequentworkhasshownthatourexperienceofglosscannotbeunderstoodsoeasily(Andersonand
Kim2009;KimandAnderson2010;Kimetal.2011;Marlowetal.2011;OlkkonenandBrainard2010,2011).Oneof
themainproblemswiththeproposedimagestatisticsisthattheyfailtotakeintoaccountthekindofimage
structurethatpredictswhenglosswillorwon’tbeperceived.Specularhighlights,andspecularreflectionsmore
generally,mustappearinthe‘rightplaces’onsurfacestoelicitaperceptofgloss(seeFigure4).Fromaphysical
perspective,specularhighlightsclingtoregionsofhighsurfacecurvature.Theperceptionofglossalsorequires
highlightstoappearinspecificplacesandhaveorientationsconsistentwithsurfaceshadingforasurfaceto
appearglossy,ageometricconstraintthatisnotcapturedbyhistogramorsub-bandskew.
Clicktoviewlarger
Figure5 .Interactionsbetween3Dshapeandperceivedglossasafunctionoftheilluminationfield.Allof
theimagesinthisimagehavethesamephysicalglosslevel,butdonotappearequallyglossy.Theimages
inthetoprowwererenderedinanilluminationfieldwheretheprimarylightsourceswereorientedobliquely
tothesurface,andtheimagesinthesecondrowwereilluminatedinthesameilluminationfieldwiththe
primarylightsourcesorientedtowardsthesurface.
AdaptedfromMarlowetal.(2012).
Clicktoviewlarger
Figure6 .Dataandmodelfitsfortheexperimentsweperformedontheinteractionsbetweenperceived
gloss,3Dshape(ascapturedbyameasureofsurfacerelief),andtheilluminationfield.Thestimuliwere
viewedeitherwithorwithoutstereoscopicdepth(the‘disparity’and‘nodisparity’conditionsrespectively).
Thedifferentcoloredcurvesineachgraphcorrespondtoadifferentilluminationdirectionofaparticular
illuminationfield(called‘Grace’).Theglossjudgmentsareinthetwotoprightpanels.Thepanelsonthe
leftrepresentthejudgmentsofaseparategroupofobserversoffourdifferentcuestogloss:thedepth,
coverage,contrast,andsharpnessofspecularreflections.Thepanellabeled‘skew’wascomputeddirectly
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The perceptual representation of transparency, lightness, and gloss
fromimages.Thedottedlinesinthetwographsonthetoprightcorrespondtothebestfittinglinear
combinationofthecuesontheleft,whichaccountfor94percentofthevarianceofglossjudgments.The
weightsaredenotedintheboxesadjacenttothesmallarrowsinthecenterofthegraphs.
AdaptedfromMarlowetal.(2012).
Althoughtheseresultssuggestthatthevisualsysteminsomesense‘understands’thephysicsofspecular
reflection,thereareotherfindingsthatrevealthattheextentofanysuchunderstandingislimited.Theperception
ofglosshasbeenshowntointeractwithasurface’s3Dshapeanditslightingconditions,whicharephysically
independentsourcesofimagevariability(Hoetal.2008;Marlowetal.2012;OlkkonenandBrainard2011).These
interactionshavebeenobservedbyavarietyofauthorsandhaveresistedexplanation.Indeed,theseinteractions
aredifficulttounderstandfromaphysicalperspective,sinceglossand3Dshapeareindependentsourcesof
imagestructure.However,werecentlypresentedevidencethattheseinteractionscanbeunderstoodasa
consequenceofasimplesetofimagecuesthatthevisualsystemusestogenerateourexperienceofgloss,which
areonlyroughlycorrelatedwithasurface’sphysicalglosslevel(Marlowetal.2012).Someoftheintuitionshaping
thistheoreticalproposalcanbegainedbyconsideringthesurfacesdepictedinFigure5.Allofthesurfacesin
theseimageshavethesamephysicalglosslevel,yetappeartovaryappreciablyinperceivedgloss.Eachcolumn
containssurfaceswithacommondegreeofrelief,andeachrowcontainsimagesthatwereplacedinan
illuminationfieldwiththesamedirectionoftheprimarylightsources.Wevariedthestructureofthelightfield,the
directionoftheprimarylightsources,and3Dsurfacerelief.Observersperformpairedcomparisonjudgmentsof
theperceivedglossofallsurfaces,wheretheychosewhichofapairofsurfaceswasperceivedasglossier.The
datarevealedcomplexinteractionsbetweenthelightfieldandsurfaceshapeonglossjudgments.Ascanbeseen
inFigure6,thevariationoftheilluminationfieldandshapehadasignificantimpactonthesharpness,size,and
contrastofspecularhighlightsintheseimages.Wereasonedthatifobserverswerebasingtheirglossjudgments
onthesecues,thenitshouldbepossibletomodelobservers’glossjudgmentswithaweightedcombinationof
theseimagecues.However,thereiscurrentlynoknownmethodforcomputingthesecuesdirectlyfromimage.We
thereforehadindependentsetsofobserversjudgeeachofthesecues,andtestedwhetheritwaspossibleto
predictglossjudgmentswithaweightedsumofthesecues.Wefoundthatasimpleweightedsummodelwas
capableofpredictingover94percentofthevarianceoftheotherobservers’glossjudgments.Thus,althoughthe
perceptionofsurfaceswiththesamephysicalglosslevelcanappeartovarysignificantlyinperceivedgloss,these
effectscanbeunderstoodwithasetofrelativelysimple,albeitimperfect,‘cues’thatthevisualsystemusesto
generateourexperienceofgloss.
4.Theperceptualorganizationofsurfacesandmaterials
Thelastfewdecadeshavewitnessedanexplosiveincreaseinmodelsthathavetreatedvisualprocessesasa
collectionofapproximatelyideal‘solutions’toparticularcomputationalproblems.Suchmodelsareexplicitly
teleological:theytreatadesiredoutcome,goal,ortaskastheorganizingforcethatshapestheperceptualabilities
theyareattemptingtomodel.Evolutionarytheoryservesastheengineeringforcethatputativelydrivesbiological
systemstowardoptimalsolutions.Thismodelingprocesshingescriticallyontheabilitytospecifythe‘naturaltasks’
thatwereputativelyshapedbyevolution.Thejustificationfortheadaptiveimportanceofaparticular‘naturaltask’
typicallytakesagenericform:anenvironmentalpropertyistreatedashavingevolutionarysignificancebecauseit
isanintrinsicpropertyoftheworld.Thus,anyanimalcapableofaccuratelyrecoveringthatpropertywouldgainan
adaptiveadvantage.Thepropertiestoberecovered—the‘tasks’ofvision—aredefinedinwithrespecttoparticular
physicalsourcesofvariability.Ourexperienceoflightnessistreatedasthevisualsystem’ssolutiontotheproblem
ofrecoveringthealbedoofasurface.Ourexperienceoftransparencyistreatedastheperceptualsolutiontoa
particulargenerativemodeloftransparency(suchasMetelli’sepiscotistermodelorFaulandEkroll’sfiltermodel).
Andourexperienceofglossisunderstoodasthevisualsystem’sattempttoestimatethespecularcomponentof
surfacereflectance.
Oneoftheassumptionsofthisapproachisthatthedimensionsofpsychologicalvariationareassumedtomirror
thesourcesofphysicalvariation.ThisassumptionisexplicitinbothMetelli’smodel,whichtreatedtheepiscotister
asbothaphysicalandpsychologicalmodeloftransparency,andtheEIMofBrainardandMaloney,whichasserts
thatthevisualsystemgeneratesa‘virtual’modeloftheilluminanttorecovercolorandlightness.Theperceptionof
glosshasalsobeenstudiedasakindof‘constancy’problem,whichinvolvesrecoveringthespecular‘component’
ofreflectance.
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The perceptual representation of transparency, lightness, and gloss
Amainthemeofthischapteristoquestiontheadequacyofthisconceptualizationofvision.Ratherthanattempting
toguessthe‘naturaltasks’andananimal,Iviewthegoalofperceptualtheorytodiscoverthe‘natural
decompositions’ofrepresentationalspace,i.e.,todiscoverthepsychologicaldimensionsthatcapturethespace
ofourexperiences.Theprecedingfocusedonourexperienceoftransparency,lightness,andgloss.Eachofthese
attributescanbeidentifiedwithaparticularphysicalpropertyofsurfacesandmaterial,whichcanbedescribedin
physicaltermsindependentlyofanyperceptualsystem.Suchdescriptionsassumethatthevisualsystemplaysno
partindefiningtheattributesthatitputativelyrepresents;thedimensionsaregivenbyidentifiablesourcesof
variationintheworld,whichthevisualsystemisattemptingtorecover,notbyintrinsicpropertiesofthevisual
system.Weareleftdiscussinghowwellthevisualsystemencodesorrecoversaparticularworldproperty,rather
thanhowthevisualsystemcontributestoshapingthedimensionsofourvisionexperience.
Theprecedingsuggeststhatthisgeneralapproachfailstoexplainanumberofdifferentphenomenainsurfaceand
materialperception.TheperceptionofsurfaceopacitydoesnotfollowMetelli’smodeloftransmittance.Weargued
thatoneofthemainreasonsforthisfailurewasthatMetelli’smodelisbasedonaratioofluminancedifferences,
wherearenotavailabletoavisualsystemthattransformsretinalluminanceintolocalcontrastsignals.Weshowed
thatourmatchingdatawerewellpredictedbyamodelinwhichobserversmatchedcontrastratios,ratherthan
luminancedifferenceratios.Oneofthekeypointsofourmodelwastodefinetransmittanceinawaythatwas
consistentwithintrinsiccodingpropertiesofthevisualsystem,evenifthisresultsinthefailuretocompute
physicallyaccuratemeasureofsurfaceopacity.Thisgeneralapproachofaphysiologicallymotivatedmodelhas
alsobeenpursuedbyarecentmodeloftheseresultsbyVladusich,whoproposedanalternativemodelofour
transmittancematchingdata(Vladusich2013).Heshowsthatourtransmittancematchingdatacanbecaptured
withamodifiedversionofMetelli’smodelinwhichlogluminancevaluesareusedinsteadofluminancevalues
(Vladusich,submitted).Likeourmodel,thechoicetouseLogluminancevaluescannotbederivedfromthephysics
oftransparentsurfaces;theyarederivedfromintrinsicresponsepropertiesofthevisualsystem.
Thedifferenttheoriesoflightnessperceptionareevenmorecontentiousanddiversethanthosefoundinthe
transparencyliterature.Oneofthebasicissuesinvolvesthedistinctionbetweenlightnessandbrightness.The
perceptionoflightnessisthendefinedastheperceptionofdiffuse(achromatic)surfacereflectance,whereas
brightnessisdefinedastheperceptionofimageluminance.Thepresumptionisthatthesephysicaldistinctions
havepsychologicalmeaning.Butthisisfarfromself-evident.Themajorityofworkonlightnesshasused2D(flat)
mattedisplaysofsurfaceswithuniformalbedos,forwhichthedistinctionbetweenlightnessandbrightnessis
arguablyleastvalid(ormeaningful)perceptually.Forsomeexperimentalconditions,observers’matchingdatawill
differsubstantiallyifinstructedtomatcheitherbrightnessorlightness.Butinothers,adifferenceininstructions
maymakelittleornodifference.Consider,forexample,theproblemofmatchingthe‘brightness’versusthe
‘lightness’ofthechecker-shadowillusion.Agivenpatchappearsaparticularshadeofgrey,andthereisno
evidencethatobserverscoulddistinguishitsbrightnessandlightness.Insupportofthisview,wefoundthatthe
perceptionoflightnessincreasedasafunctionofitsluminanceinbothsimulatedand‘real’Mondriandisplays.
Moreover,thedataofRadonjićetal.(2011)demonstratethatobserverswillreadilymapaphysicallyunrealizedset
ofluminances,spanning4ordersofmagnitude,ontoalightnessscaletwoorderssmaller.Theseresultsare
impossibletoreconcilewithmodelsthattreattheproblemoflightnessasarecoveryproblem,sincetherangeof
reflectancesinanaturalscenecanonlyspanarangeof~30:1.
Intheperceptionofgloss,wefoundthatobserver’sexperienceofglosscanbewellpredictedbyasetofsimple
cuesthatareonlyimperfectlycorrelatedwiththephysicalglossofasurface.Glossisnotdefinedwithrespectto
somephysicallyspecifieddimensionofsurfaceoptics,butwithrespecttoasetofcuesthevisualsystemusesas
aproxyforanobjectivelydefinedsurfaceproperty.
Whatgeneralunderstandingcanbegleanedfromthesepatternsofresults?Alloftheseresultsrevealthe
insufficiencyofattemptingtoidentifypsychologicaldimensionsofourexperiencewithphysicalsourcesofimage
variability.Thefactthatwehaveaparticularexperienceoflightness,gloss,ortransparencydoesnotimplythat
thedimensionsofourexperiencemapontoaparticularphysicaldimensionand/oritsparameterization.The
generalargumentusedtojustify‘naturaltasks’takesthegenericformthat‘gettinganenvironmentalpropertyright
increasesadaptivefitness.’Thepresumedidentificationoffitnesswithveridicalperceptionisactuallyfallacious
(seeHoffman2009;cf.Lewontin1996),butevenifsuchviewswereaccepted,theyareincapableofdistinguishing
perceptualabilitiesthatwereactuallyshapedbynaturalselectionfromthe‘spandrels’thatcamealongforthe
evolutionaryride.Thefactthathumanobserverswillreadilymapanecologicallyunobtainablerangeofluminance
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The perceptual representation of transparency, lightness, and gloss
values(inasingleilluminant)ontolightnessestimatessuggeststhatlightnessmaybeoneexampleofaperceptual
spandrel.Althoughhumanobserverscanusuallydistinguishreflectancedifferencesfromothersourcesofimage
variation,theperceptionofabsolutelightnessmaysimplybetheresultoflow-levelprocessesofadaptationthat
allowthevisualsystemtoencodeaparticularrangeofluminancevalues.Indeed,Iamawareofnocompelling
evidenceorargumentaboutwhylightnessconstancyperseprovidedanadaptiveadvantage,orissomethingthat
thevisualsystemisexplicitly‘designed’tocompute.Asimilarargumentholdsfortheperceptionoftransparency
andgloss.Wecanreadilydistinguishbetweensurfacesormediathattransmitlightfromthosethatdonot,or
distinguishbetweensurfacesthatreflectlightspecularlyfromthosethatdonot.Butthedataalsosuggeststhatwe
donotscalethesedimensionsinawaythatisphysicallycorrectforanyoftheseproperties.
Althoughitisdifficulttocraftacompellingargumentforthespecificadaptiveutilityofdevelopingaphysically
accuratemodeloflightness,gloss,andtransparency,thefactthatweexperiencethesedifferentsourcesof
variableasdifferentunderlyingcausesimpliesthatthevisualsystemiscapableofatleastqualitatively
distinguishingdifferentsourcesofimagestructure.This‘sourcesegmentation’isarguablyoneofthemost
importantgeneralpropertiesofourvisualsystem.Thevisualsystemmay,infact,bequitepoorinestimating
lightnessinarbitrarycontexts,butitisnonethelesstypicallyquitegoodatdistinguishingimagestructuregenerated
bylightnessdifferencesfromilluminationchanges,orvariationsintheopacityofatransparentsurface,orfrom
specularreflections.Theidentificationofspecularreflectionsasspecularreflectionsdependsontheircompatibility
withdiffusesurfaceshadingand3Dsurfacegeometry,andismodulatedbythestructure,intensity,anddistribution
ofimagestructuresoidentified,evenifitdoesnotaccuratelycapturethe‘true’glosslevelofasurface.And
althoughthephysicaltransmittance(oropacity)ofasurfacedoesnotvaryasafunctionofitsalbedoorcolor,the
psychologicalanalogofopacity—its‘hidingpower’—willforavisualsystemthatusescontrasttodeterminethe
visibilityofimagestructure.Thevisualsystemmaynotdeterminethe‘true’opacityofasurface,butnonethelessis
effectiveatperformingasegmentationthatcapturesthepresenceorabsenceoftransmissivesurfacesandmedia.
5.Summaryandconclusions
Inthischapter,Ihaveconsideredanumberoftopicsintheareaofsurfaceandmaterialperception:transparency,
lightness,andgloss.Theorganizationofthesetopicswaslargelyshapedbymyhistoricalprogressionin
conductingresearchintoeachofthesedomains;manyalternativeorganizationsarepossible.Inalloftheseareas
ofinquiry,therehasbeenastrikingtendencytotreatphysicalmodelsofimageformationassomekindof
approximationtoaperceptualmodeloftheirapprehension.Theprecisewaythataphysicalmodel‘counts’asa
psychologicalmodelistypicallyleftunspecified.Itappearstobebasedonsomeintuitionthatthevisualsystem
‘knows’or‘understands’thephysicsthatofaparticularsurfaceormaterialattribute.Icontendthatoneofthemain
goalsofvisionscienceshouldbetodiscoverthedimensionsofperceptualexperience,andtheimagevariables
thatmodulateourresponsetothem.Whereasthedimensionsofphysicalvariablescanbespecifiedindependently
ofanyperceptualsystem,thedimensionsofperceptualexperienceareinherentlyrelational,andmustconsider
theintrinsicpropertiesofthevisualsystemaswellastheenvironmentsinwhichtheyoperate.
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Notes:
(1)Thisreductionincontrastoccursforalmostanydefinitionofcontrast,whichincludesadivisivenormalization
termthatisafunctionofintegratedormeanluminanceintheregionoverwhichcontrastisdefined.Unfortunately,
thereiscurrentlynogeneraldefinitionofcontrastthatadequatelycapturesperceivedcontrastinarbitraryimages,
sotheprecisewayinwhichcontrastisreduceddependsonthedefinitionofcontrastusedinaparticularcontext.
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The perceptual representation of transparency, lightness, and gloss
BartonL.Anderson
BartonL.Anderson,SchoolofPsychology,TheUniversityofSydney,Australia
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