Data fusion techniques for object space classification using airborne laser data and airborne digital photographs

168 Pages·2002·7.3 MB·English

by  Park, Joong Yong, 1968-

DATAFUSIONTECHNIQUESFOROBJECTSPACECLASSIFICATION
USINGAIRBORNELASERDATA
ANDAIRBORNEDIGITALPHOTOGRAPHS
By
JOONGYONGPARK
ADISSERTATIONPRESENTEDTOTHEGRADUATESCHOOL
OFTHEUNIVERSITYOFFLORIDAINPARTIALFULFILLMENT
OFTHEREQUIREMENTSFORTHEDEGREEOF
DOCTOROFPHILOSOPHY
UNIVERSITYOFFLORIDA
2002
Copyright2002
by
JOONGYONGPARK
Tomywife,SunghwaYoun,
Mylovelydaughter,Shinhwo,
Andmyparents,ByungJoParkandSoonJaLee
ACKNOWLEDGMENTS
Iwouldliketoexpressmygratitudetomysupervisor,ProfessorGradyTuell,forhis
continuoussupport,encouragement,andguidancethroughoutmystudies.Heintroduced
metotheworldofdatafusion,whichIhadneverbeenthoughtbefore.Healwayshelps
metosolveproblemsandencouragesgoingtoahigheracademiclevel.Heisagreat
teacherformeacademicallyandspiritually.IamsoproudtobehisfirstPh.D.student.
IwishtothankProfessorRameshShresthaandWilliamCarter,whoalsogaveme
continuoussupportandespeciallyfortheirpositiveinfluenceforyearstocome.They
introducedmetotheentranceofLIDAR.Theymaintainaworldclassresearchteamof
airbornelasermappingtechnology,whichtheygavemeachancetobeinvolvedin.
Ialsowishtothankmyothercommitteemembers.ProfessorDavidBloomquistand
PaulZwick,fortheircomments.Ialsowishtoexpressthankstomypastandpresent
colleaguesintheresearchgroup.
IV
TABLEOFCONTENTS
gage
ACKNOWLEDGMENTS iv
LISTOFTABLES viii
LISTOFFIGURES x
ABSTRACT xiii
CHAPTER
1 INTRODUCTION 1
ObjectiveofResearch 4
DataFusion 5
AnObjectRecognitionExample 7
PotentialAdvantagesinIntegratingMultipleSensors 9
TheMethodsofDataFusion 9
Signal-LevelMethods 10
Pixel-LevelMethods 11
Feature-LevelMethods 12
Decision-LevelMethods 14
DataAcquisition 17
Outline 19
2 CLASSIFICATIONUSINGASUPERVISEDSTATISTICALPATTERN
RECOGNITIONTECHNIQUE 22
DataFusionofDigitalColorImagery,ALSMIntensity,andDEM 22
Methodology 25
AnalysisandResults 25
Discussion 37
Summary 42
3 CLASSIFICATIONUSINGANEXPERTSYSTEMAPPROACH 44
Rule-basedClassification 44
AnalysisofStudyArea 47
V
1
Methods 49
Results 58
Discussion 62
Summary 62
4 CLASSIFICATIONUSINGTHEDEMPSTER-SHAFEREVIDENTIALTHEORY64
TheDempster-ShaferEvidentialTheory 64
TheConceptofEvidentialReasoning 65
Dempster’sRuleofCombination 68
Experiment 71
PriorProbabilityfromtheMaximumLikelihoodDecisionRule 71
DataFusionProcessingUsingtheDempster-ShaferEvidentialTheory 72
Results 80
Summary 8
5 CONCLUSIONS 84
6 DISCUSSIONANDRECOMMENDATIONFORFURTHERWORK 90
APEENDD(
A DESCRIPTIONOFTHEDATAACQUISITIONSYSTEM 93
SystemComponents 93
AirborneLaserSwathMappingSystem 93
AirborneDigitalPhotographyImagingSystem 97
B DIRECTDIGITALIMAGEGEOREFERENCING 99
AirborneGPSPositioningandGeoreferencing 99
GeoreferencingofImageSensors 103
DirectGeoreferencingMethod 103
PrinciplesofDirectImageGeoreferencing 105
PositionalOffsetandMisalignmentAngleCalibration 107
TimeAlignment 112
AngleAnalysisforBack-Projection 112
CalibrationofMisalignmentAngle 116
StudyAreaandDataAcquisition 119
Results 120
Discussion 123
C SPECIFICSOFINTENSITYDATAFROMALSMSYSTEM 124
VI
IntensityofReflectedLaserPulse 124
CorrelationBetweenALSMIntensityandTargetReflectance 126
D GAUSSIANMAXIMUMLIKELIHOODCLASSIFICATION 130
E TECHNIQUEFORASSESSINGTHEACCURACYOFCLASSIFICATIONS 135
SampleDesign 135
SampleUnit 135
SampleSize 136
SamplingSelection 136
EvaluationofErrorMatrices 138
KappaAnalysis 140
LISTOFREFERENCES 142
BIOGRAPHICALSKETCH 151
vii
1-
2- LISTOFTABLES
Table page
1.LaserSystemParameters 17
1.ConfusionMatrixBetweenClassifiedDataandReferenceDataUsinganRGB
Image(Pixels) 27
2-2.ConfusionMatrixBetweenClassifiedDataandReferenceDataUsinganHIImage
(Pixels) 28
2-3.ConfusionMatrixBetweenClassifiedDataandReferenceDataUsinganRGI
Combination(Pixels) 30
2-4.ConfusionMatrixBetweenClassifiedDataandReferenceDataUsinganRGH
Combination(Pixels) 31
2-
2-5.ConfusionMatrixBetweenClassifiedDataandReferenceDataUsinganRHI
3- Combination(Pixels) 33
2-6.ConfusionMatrixBetweenClassifiedDataandReferenceDataUsinganRGHI
Combination(Pixels) 34
2-7.ConfusionMatrixBetweenClassifiedDataandReferenceDataUsinganRBHI
Combination(Pixels) 35
2-8.ConfusionMatrixBetweenClassifiedDataandReferenceDataUsinganRGBHI
Combination(Pixels) 36
2-9.OverallAccuracyofEightBandCombinations(%) 38
10.StatisticsSummaryoftheMaximumLikelihoodClassificationfortheRGBHI
BandCombination 38
1.Level-1ClassificationSchemeUsedinanRGBImageandanHIImage 52
3-2.RulesofLevel-1ClassificationfortheHIImage 53
3-3.RulesofLevel-1ClassificationforDigitalColorImage 54
3-4.Level-2ClassificationSchemeafterDataFusionUsingProductionRules 55
viii
33--5.Level-2ProductionRulesforDataFusionofALSMandADPLevel-1Classification
4- Data 55
6.ConfusionMatrixofRule-basedClassification(Pixels) 61
1.Dempster’sCombiningRule[fromThomopoulos(1990)] 69
4-2.TheCorrelationBetweenDataandInformationofClassesforanRGBDigitalColor
Image 73
4-3.SummaryoftheMaximumLikelihoodClassificationforanRGBImage 73
44--4.TheCorrelationBetweenDataandInformationofClassesforanHIImage 76
45--5.StatisticsSummaryoftheMaximumLikelihoodClassificationforanHIImage 76
4-6.Dempster’sCombinationRuleofanRGBImageandanHIImage 78
4-7.TheMassAssignmentbyDempster’sCombinationRulefromtheALSMandADP
Data 79
8.ConfusionMatrixofDataFusionClassificationbyDempster-ShaferEvidential
Theory(Pixels) 82
1.TheComparisonofEachClassandOverallAccuracyamongThreeDataFusion
Techniques(%) 87
A-1.SpecificationsoftheOptechModelALTM1210 96
B-1.PositionalOffsetsBetweenSensorstoIMULeverArm 110
B-2.PositionalOffsetsBetweenSensorstoGPSLeverArm 110
B-3.TheOffsetBetweenSensorsandIMUMisalignment 118
B-4.OffsetBetweenGPSDataandCalculationafterApplyingSubsystemParameters119
B-5.TheComparisonBetweenGPSGroundSurveyDataandtheSamePointsonthe
Pseudo-orthorectifiedImage 123
C-1.ClassificationofALSMDataGroup 127
E-1.TheSamplePolygoninEachClass 139
E-2.ExampleErrorMatrix 141
ix
LISTOFFIGURES
Figure page
I-l.Generalarchitectureofthedatafusionprocessinimageclassification 6
11--2.Thediscriminationoffourdifferentobjectsusingcomplementaryinformationfrom
2- twosensors 8
1-3.Data-,feature-,anddecision-levelfusion 13
1-4.TheintensityimagefromtheALSMdata 18
1-5.TheelevationimagefromtheALSMdata 18
6.DigitalcolorimagefromADPsystemfromtheALSM 19
1.Feature-leveldatafusion 23
2-2.Six-trialbandcombinationfromanRGBimageandanHIimage 24
2-3.Bandcombinationimages:(a)RGI(red,greenandintensity);(b)RHI(red,height,
andintensity)combinations 24
2-4.GroundtruthreferencedataonanRGBcolorimage 26
2-5.Maximumlikelihoodclassification:(a)RGB(red,green,andblue);(b)HI(height
andintensity)bandcombinations 29
2-6.Maximumlikelihoodclassification:(a)RGI(red,green,andintensity);(b)RGH
(red,green,andheight)bandcombinations 32
2-7.Maximumlikelihoodclassification:(a)RHI(red,heightandintensity;(b)RGHI
(red,green,height,andintensity)bandcombinations 35
2-8.Maximumlikelihoodclassification:(a)RBHI(red,blue,heightandintensity);(b)
RGBHI(red,green,blue,height,andintensity)bandcombinations 37
2-9.Diagramofnormaldistributionofeightclassesonaredband 39
2-10.Diagramofnormaldistributionofeightclassesonagreenband 39
2-11.Diagramofnormaldistributionofeightclassesonablueband 40
X