Processing Methods for Airborne Oblique Thermal Video Data - ITC

99 Pages·2006·12.96 MB·English

Processing Methods for Airborne
Oblique Thermal Video Data
Isaac Nimako Boison
March, 2006
Processing Methods for Airborne Oblique
Thermal Video Data
by
Isaac Nimako Boison
ThesissubmittedtotheInternationalInstituteforGeo-informationScienceand
Earth Observation in partial fulfilment of the requirements for the degree in
Master of Science in Geoinformatics.
Degree Assessment Board
Thesis advisors Dr. Norman Kerle
Dr. Stephan Heuel
Thesis examiners Chairman: Prof. Dr. Ir. A. Stein
External supervisor: Dr. Ir. B. G. H. Gorte
INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION
ENSCHEDE, THE NETHERLANDS
Disclaimer
This document describes work undertaken as part of a programme of study at
theInternationalInstituteforGeo-informationScienceandEarthObservation
(ITC). All views and opinions expressed therein remain the sole responsibility
of the author, and do not necessarily represent those of the institute.
Abstract
There have been many improvements in remote sensing methods used in
solvingsomeoftheproblemscausedbydisasters. Theuseofbettersensors
and algorithms are helping to predict the cause of some of the disasters.
Timeisanimportantparameterwhendealingwithdisasterissues, there-
fore it is necessary to have a faster means of data acquisition. Disaster
managers and decision makers need timely information during a disaster
inordertoactaccordinglytosavelifesandproperties. Oneremotesensing
techniquethathelpstoredeemtimeintermsofdataacquisitionisairborne
thermal videography. This is a cost effective and fast remote technique to
gatherinformationonthesurfacetemperature. Ithasprovidedmanybene-
fitstoorganizationsconcernedwiththemonitoring,mappingandplanning
ofassets,landandenvironment,etc.
However,thereareyetsomeissuesthathavetobeaddressedwhendealing
with this kind of technique. Sometimes video captures during fire disas-
ters in industrial and urban settings are unplanned. This is mostly due
to the urgencies of those events and also the purposes of such surveys are
such as to show the incidence to the public through the media. Video cov-
erages mostly focus on damage areas only, leaving the surrounding areas
uncovered. The video cameras used are sometimes not calibrated and are
of comparatively low resolution. This makes the processing of such data
verychallenging. Someofthechallengesincludetheobliquenatureofthe
datawhichresultsinscalevariabilityontheimage,platforminstability,er-
raticnatureofvideocoverage,frequentchangesinfocallengthsandlackof
cameracalibrationorientation,unavailabilityofsensormodelandteleme-
tryinformationamongothers.
This research focused on the use of airborne oblique thermal video data.
The main objective of the research was to provide a work flow that will be
used to process oblique thermal video data to obtain a 2D map of fire in
theimage. Somepreprocessingandprocessingmethodswereinvestigated
andaccessedtohandlethethermaldata. Methodsofdeinterlacingofvideo
data, identification and selection of frames, mosaicing, and image trans-
formation were employed in the process. Some of the processing methods
couldnotgiveoptimalresultsduetothenatureofthevideodataused. Re-
sults of the mosaic were dependent on the quality of the video data. Also
the 2D to 2D image transformation results were also dependent on the
quality of the video data. It was noticed that more identifiable features
on the image could improve the results of the transformation. Issues like
challengesintheuseofthedata,handlingframesofdifferentzoomlevels,
differentiationbetweensmokeandfire,occlusioncausedbysmokeandfire
and accuracy assessment of the 2D map were addressed. The processing
i
Abstract
chainthusdevelopedcouldbeusedforallkindsofthermalvideodatawith
goodgeometricresolution.
Keywords
Thermalvideodata,videography,videoframes,fire,obliqueimages
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Contents
Abstract i
List of Figures vii
List of Tables ix
Acknowledgements xi
1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Remote Sensing for Disaster Management . . . . . . . . . . . . 2
1.3 The role of video data in disaster management . . . . . . . . . . 4
1.4 Some important definitions . . . . . . . . . . . . . . . . . . . . . 6
1.5 Research problem statement and justification . . . . . . . . . . . 7
1.6 Research objectives . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.6.1 Main objectives . . . . . . . . . . . . . . . . . . . . . . . . 7
1.6.2 Sub-objectives . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.7 Research questions . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.8 Scope of the work . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.9 Thesis organization . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2 Airborne Videography as a Remote Sensing Tool 11
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2 Applications of airborne video data . . . . . . . . . . . . . . . . . 12
2.3 Advantages and Disadvantages of airborne video data . . . . . . 15
2.4 Thermal Infrared Remote Sensing . . . . . . . . . . . . . . . . . 16
2.4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.4.2 Background of thermal remote sensing . . . . . . . . . . 17
2.4.3 Thermal Systems . . . . . . . . . . . . . . . . . . . . . . . 19
2.5 Previous applications of thermal video data . . . . . . . . . . . . 20
2.6 Summary and Outlook . . . . . . . . . . . . . . . . . . . . . . . . 21
3 Study Area and Data 23
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2 General Description of the Study Area . . . . . . . . . . . . . . . 24
3.3 The Thermal Imager . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.3.1 System features . . . . . . . . . . . . . . . . . . . . . . . . 27
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3.4 Video camera . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.4.1 Thermal oblique video data . . . . . . . . . . . . . . . . . 30
3.4.2 Optical oblique video data . . . . . . . . . . . . . . . . . . 30
3.4.3 Pre-disaster and post disaster vector data . . . . . . . . . 30
3.4.4 An orthophoto . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.5 Summary and Outlook . . . . . . . . . . . . . . . . . . . . . . . . 31
4 Methodology and Approach 33
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.2 Quality and content of thermal video data . . . . . . . . . . . . . 35
4.3 Preprocessing of video data . . . . . . . . . . . . . . . . . . . . . 36
4.3.1 Digitization of video data. . . . . . . . . . . . . . . . . . . 36
4.3.2 Video Deinterlacing . . . . . . . . . . . . . . . . . . . . . . 37
4.3.3 Frame Grabbing . . . . . . . . . . . . . . . . . . . . . . . . 37
4.3.4 Identification of sequences of constant zoom level . . . . 37
4.4 Image Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
4.4.1 Affine transformation estimation . . . . . . . . . . . . . . 38
4.4.2 Mosaicing of frames . . . . . . . . . . . . . . . . . . . . . 40
4.4.3 Orthorectification of the aerial video mosaic . . . . . . . 40
4.4.4 Density slicing and thresholding of Image . . . . . . . . . 43
4.4.5 Delineation of fire pixels . . . . . . . . . . . . . . . . . . . 44
4.4.6 2D map of fire areas . . . . . . . . . . . . . . . . . . . . . 45
4.5 Summary and outlook . . . . . . . . . . . . . . . . . . . . . . . . 45
5 Results and analysis 47
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
5.2 Review of Processing Chain . . . . . . . . . . . . . . . . . . . . . 47
5.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
5.3.1 Motion2D results . . . . . . . . . . . . . . . . . . . . . . . 48
5.3.2 Affine transformed images . . . . . . . . . . . . . . . . . . 48
5.3.3 Mosaics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
5.3.4 Results and geometric accuracy of image transformation 51
5.3.5 Density slicing results and accuracy . . . . . . . . . . . . 55
5.3.6 Delineation of fire areas . . . . . . . . . . . . . . . . . . . 60
5.3.7 Results and analysis of 2D maps . . . . . . . . . . . . . . 60
5.4 Summary and Outlook . . . . . . . . . . . . . . . . . . . . . . . . 64
6 Discussion 65
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
6.2 Review of objectives . . . . . . . . . . . . . . . . . . . . . . . . . . 65
6.2.1 Discussion of objectives . . . . . . . . . . . . . . . . . . . . 65
6.3 Review of research questions . . . . . . . . . . . . . . . . . . . . 67
6.3.1 Discussion of research questions . . . . . . . . . . . . . . 67
7 Conclusion and Recommendation 69
7.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
7.2 Recommendation . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
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Contents
Bibliography 73
Appendices 78
A Motion2D code 79
A.0.1 Affine parameters . . . . . . . . . . . . . . . . . . . . . . . 80
B Matlab code 83
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Contents
vi
List of Figures
1.1 Disaster Management Cycle, Montoya 2002, [36] . . . . . . . . . 3
1.2 The outline of the thesis . . . . . . . . . . . . . . . . . . . . . . . 9
2.1 Aerial photograph classification . . . . . . . . . . . . . . . . . . . 12
2.2 An Helicopter with a video camera system on board . . . . . . . 13
2.3 The Electromagnetic Spectrum . . . . . . . . . . . . . . . . . . . 17
2.4 A plot showing the percent transmittance and the wavelength of
the thermal electromagnetic range . . . . . . . . . . . . . . . . . 17
2.5 Wien’s displacement curve showing the variation of energy and
wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.6 Images covering the same area . . . . . . . . . . . . . . . . . . . 20
3.1 A map showing the location of Enschede on the Netherlands map 24
3.2 Map showing the location of the disaster area in Enschede . . . 25
3.3 Anobliquephotographtakenfromanhelicoptershowingthedis-
aster area on fire . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.4 Anobliquephotographtakenfromanhelicoptershowingthedis-
aster area after the fire . . . . . . . . . . . . . . . . . . . . . . . . 26
3.5 The Thermovision TM1000 ECS imager [2] . . . . . . . . . . . . 27
3.6 Layout of the status area of the Thermovision TM1000 ECS im-
ager [2] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.7 Graphs visualizing the three concepts of color mapping . . . . . 29
4.1 Processing chain for processing airborne oblique thermal video
data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
4.2 The three types of thermal video data . . . . . . . . . . . . . . . 35
4.3 Affine transformation effects. . . . . . . . . . . . . . . . . . . . . 39
4.4 Figure shows the relationship between an oblique image and an
orthogonal image . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.5 Erdas Imagine interface for 2D-to-2D image transformation . . 42
4.6 Figure shows the result of an orthorectified oblique video mosaic 43
4.7 The effect of leaping fire in the image . . . . . . . . . . . . . . . 44
5.1 Results of affine transformation of images in Motion2D showing
grey images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.2 Result of mosaic of 41 frames for the first set of sequence on day 1 50
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