section 7 orthoimage generation and object extraction (mainly roads and buildings)
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Section 7 Orthoimage generation and object extraction (mainly roads and buildings) Emmanuel Baltsavias. Orthoimage Generation. Older sensor models methods: Kratky’s Polynomial Mapping Functions (PMFs) Relief corrected affine transformation. - PowerPoint PPT PresentationTRANSCRIPT
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Section 7
Orthoimage generation and object extraction (mainly roads and buildings)
Emmanuel Baltsavias
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Orthoimage Generation
Older sensor models methods:
• Kratky’s Polynomial Mapping Functions (PMFs)
• Relief corrected affine transformation
- Project GCPs on reference plane (X, Y coordinate corrections) using sensor elevation and azimuth
- Reference plane -> reference plane of DTM
- Compute affine transformation between X, Y object and x, y pixel coordinates
- 3 GCP’s are needed but 4-6 are suggested
Current method:
• Use RPCs and subsequent shifts or affine transformation
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Orthoimage Generation
Test resultsLuzern
Method: Relief corrected affine transformation
Sens elev. (deg) 67.7DTM spacing/accur (m) 25 / 2.5 lowland, 10 AlpsGCP accuracy (m) 0.5 – 3GCP definition Very poor to goodElevation range (m) 400-2100
Version GCPs/CPs RMS/X RMS/Y Max. abs X Max. abs Y
1 0 /66 134.2 30.6 501.5 118.1
2 6 / 65 2.6 2.2 9.9 5.9
5 6/14 0.6 0.6 1 1.1
CPs = check points
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Orthoimage Generation
Test results
Method: Relief corrected affine transformation
Nisyros
Version GCP's/CPs RMS/X RMS/Y Max. abs X Max. abs Y1 0 / 38 106.1 75.5 153.1 122.82 4/34 1.7 1 4.4 2.33 4/15 0.9 0.6 1.5 1.4
Sens elev. (deg) 73.5DTM spacing/accur (m) 2 / 3.3 GCP accuracy (m) ca. 0.5GCP definition Poor to goodElevation range (m) 0-700
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Orthoimage generation (IKONOS, Quickbird) in Geneva
Input data
2 IKONOS Geo images (IKONOS-West / IKONOS-East)1 Basic QUICKBIRD Image
Orthoimages (for acquisition of GCPs):OP-DIAE: Digital Orthos of Canton Geneva (25 cm pixel size, 0.5 m planimetric RMS)Swissimage: Digital Orthos of Switzerland of Swisstopo (50 cm pixel size, 1m planimetric RMS)
DTMs:DTM-AV (from airborne laser scanning): 1 m grid spacing, 0.5 m height RMSDHM25 of Swisstopo (from digitised contours): 25 m grid spacing, 1.5-2 m height RMS
Measurement of GCPs with ellipse fit and line intersection.
Image orientation with various sensor models. RPCs with subsequent affine transformation used for orthoimage generation.
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Orthoimage generation (IKONOS, Quickbird) in Geneva
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Orthoimage generation (IKONOS, Quickbird) in Geneva
Pansharpened orthoimages. Left Ikonos, right Quickbird.
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Orthoimage generation (IKONOS, Quickbird) in Geneva
Definition of lines and circles. Left Ikonos, right Quickbird.
Note the large visual difference although pixel size is 1m and 0.7m respectively.
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Orthoimage generation (IKONOS, Quickbird) in Geneva
Image Number of GCPs/CPs
X RMS (m) Y RMS (m) X mean with sign (m)
Y mean
with sign (m)
Ikonos West 10/23 0.55 0.63 0.25 -0.49
Ikonos East 10/33 0.47 0.76 0.10 -0.59
Quickbird 10/53 0.56 0.60 -0.08 -0.38
Planimetric accuracy of panchromatic orthos with GCPs from OP-DIAE
(CPs = check points)
Quickbird is not more accurate than Ikonos although GSD was 0.7m and 1m respectively.
Planimetric accuracy could be even higher with well defined GCPs measured with GPS.
In Y mean (bias) large due to coordinate system differences (Geneva and national systems differ).
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Orthoimage generation (IKONOS, Quickbird) in Geneva
Image Number of GCPs/CPs
X RMS (m) Y RMS (m) X mean with sign (m)
Y mean
with sign (m)
Ikonos West 10/58 0.91 0.72 -0.07 -0.30
Ikonos
East
10/57 0.67 0.75 0.00 -0.33
Quickbird 10/93 0.66 0.77 -0.06 -0.11
Planimetric accuracy of panchromatic orthos with GCPs from OP-DIAE and Swissimage
Submeter accuracy even with GCPs from not so accurate Swissimage orthos.
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Road Extraction – Project ATOMI
• Automated Reconstruction of Topographic Objects from Aerial Images using Map Information.
• It’s a co-operation between swisstopo (Swiss Federal Office of Topography) and ETH Zurich, financed by swisstopo.
• ATOMI uses edge detection and existing knowledge and cues about road existence to detect road centrelines from orthophotos.
• ATOMI is used to remove cartographic generalisation and fit the geometry of roads to the real world to an accuracy of better than 1m in x, y and z
• ATOMI keeps the topology and attributes of the input vector map data set (VECTOR25)
• The result is a new accurate 3D road centreline data set without gaps, containing the topology and attributes of the input data as well as new weighted mean road width attributes
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
ATOMI input and output data
3D accurate structured road vector data
2D inaccurate structured road vector data
DTM/DSM
Ortho images
ATOMIAutomatic
road centreline extraction
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Classification of roads according to landcover
foresturbanrural area
Current work only in rural areas
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
General Strategy• Use of existing knowledge, rules and models
• Use and fusion of multiple cues about road existence
• Creation of redundancy through multiple cues to account for errors
• Early transition to object space, use of 2D and 3D interactions to bridge gaps and missing road parts
• Object-oriented approach in multiple objects (e.g. road classes)
+
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
15
Features, Cues and Algorithms
2-D straight edges2-D road marks
zebra crossingsStereo color
aerial images / orthosFeature
Extraction
Geodatabase InformationDerivation
road geometryroad attributesroad topologylandcover
3-D straight edges
3-D road marksImage
Matching
road regionsshadowsvegetationbuildings
ImageClassification
above-ground and
ground objectsDSMnDSM
Generation
Input Features, cuesProcessing
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
a. Straight edge
extraction
b. Removal of irrelevant
edges
c. Detection of Parallel
Road Sides
d. Evaluation of Missing
Road Sides
e. Bridging Gaps
f. Linking Road Sides to
Extract Roads
How ATOMI road extraction works
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Test site in Switzerland
Geneva 7km²Aerial Film 50cm (summer ‘98) IKONOS PSM 100cm (May ‘01)Quickbird PSM 70cm (July ‘03)Manually measured reference data from 50cm orthophotos
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
50cm Aerial Film 100cm IKONOS 70cm QUICKBIRD
Results from Geneva (yellow VECTOR25, black result)
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
50cm Film 100cm IKONOS 70cm QUICKBIRD
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Quality evaluation of the results of Geneva
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Results from Geneva
• The system achieved good results with the 50cm aerial film imagery with 90% of rural roads extracted.
• The performance (mainly the completeness) of the satellite data was inferior to aerial imagery, especially the 1m IKONOS imagery
• In the satellite data, higher class (wider) roads were usually extracted, while most lower class (narrower) roads were not. This is because of ATOMI’s algorithm requirement of min. 3 pixels road widths was not fulfilled.
• The smaller GSD of Quickbird made more roads visible and the road surface and road edges were clearer. But compared to aerial film the completeness was lower.
• With smaller GSD, correctness and accuracy do not deteriorate much, but completeness yes.
• Other road extraction methods and results with aerial and Ikonos images as part of EuroSDR working group on road extraction
• See paper Mayer et al. in coming ISPRS Com. III Symposium, Bonn, September 2006
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Building Extraction, Ikonos, Melbourne
Roof corners
• 19 roof corners measured by GPS
• Measured in mono and stereo in all three images of Melbourne
Results from stereo images and 6 GCPs (RMSE):
RPCs: XY = 0.7m Z = 0.9m
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Building Extraction
Aerial Photography (1:15,000) Ikonos 1m Pan Stereo
Omission of 15% of buildings (small & large)
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Building Extraction
3D Model of University of Melbourne Campus from Ikonos 1m PAN Stereo
Produced with CyberCity Modeler
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Building Extraction
Aerial Photography (1:15,000) Ikonos 1m Stereo Imagery
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Building Extraction
Aerial Photography (1:15,000) Ikonos Stereo Ikonos Nadir Pan-Sharp.
Conducive to building feature measurement
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Building Extraction
Aerial Photography (1:15,000) Ikonos Stereo Ikonos Nadir Pan-Sharp.
Ikonos stereo of questionable value to building feature measurement in this case
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Building Extraction
Aerial Photography (1:15,000)
Ikonos Stereo Ikonos Nadir Pan-Sharp.
Ikonos stereo of questionable value to building feature measurement in this case
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
DEM
(X,Y,Z)
Image plane, (line,sample)
Sensor model
DEM
Initial Z from DEM
Line, Sample
XY Solver
Interpolating Z
Convergence
XYZ
Z
No
Yes
Monoplotting: 3D Information Extraction from Single Satellite Images(implemented In Barista software, C. Fraser, Univ. of Melbourne)
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
3D mapping of points and linear features by monoplotting
Measure single points in monoplotting mode using one image in combination with a DEM
Measure polylines/closed polylinein monoplotting mode
3D mapping of pointsand linear features
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Measure groundpoint using one image in combination with a DEM
XYZ
Measure roofpoint Z from line,sample and
XY
Height ΔH
Height measurement of buildings by monoplotting
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
3D mapping of buildings from single IKONOS image
Measure first ground point of thebuilding (by monoplotting)
Measure first roof point, assuming thesame XY-position as ground point
Force same height for other roof points and find XYGet other ground points bykeeping XY-position and interpolateheight from underlying DEM
>>> 3D building reconstruction
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Building reconstruction from single IKONOS image
Export of buildings in VRML dataData collection with Barista
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Quality assessment of results derived from IKONOS and Quickbird imagery
• GCPs and multi-image data used as reference
• Single image point positions and building heights were measured
• Bias-corrected RPCs and affine sensor model was used
• Measurements were performed in three IKONOS and two Quickbird images
• Regular monoplotting mainly depending on DEM quality
• Single-image height measurement affected significantly by off-nadir angle
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
Quality assessment of results derived from Ikonos and Quickbird
Sensor orientation
model
Height RMS discrepancy at CPs (m)
e = 83° e = 61° e = 61°
RPCs 6.59 1.08 1.31
No. of CPs 20 23 22
3D-Affine 3.05 0.69 0.76
No. of CPs 20 24 22
Accuracy of Building Height Determination
Sensor orientation
model
Height RMS discrepancy at CPs (m)
e = 60° e = 58°
RPCs 1.01 1.03
No. of CPs 30 30
3D-Affine 1.34 1.33
No. of CPs 29 29
Accuracy gets worse with higher elevation
Quickbird Ikonos
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
3D site modeling (Silvereye from Geotango, CA)
Semi-automatic system, using one oriented image (monoplotting) and additional information (similar to Barista). Software for 3D site modeling and orthoimage generation. Not available any more (company bought by Microsoft)
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
3D city modeling (Cybercity AG)
Quickbird stereo images, Phoenix, USA
ISPRS Technical Commission I Symposium “From Sensors To Imagery”, Paris – Marne la Vallée, France, 3-6 July 2006
Institute of
Photogrammetry and
GeoInformation
WEB-based 3D earth visualisation and Location Based Services
• Google Keyhole (Quickbird)
• Similar devepments by Microsoft (Orbimage)
• Geotango‘s (CA) Globeview (company bought by Microsoft)
• Use of satellite images, espec. HR
• DSM from usually unknown sources
• 3D building models
• Driving directions
• Location of various services