1 from imagery to map: digital photogrammetric technologies 14 th international scientific and...
TRANSCRIPT
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14th International Scientific and Technical Conference
From Imagery to Map: Digital Photogrammetric Technologies
Dense DSM Generation Module in PHOTOMOD 6.0
Andrey SechinScientific Director, Racurs
October 2014, Hainan, China
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DEM, DTM, DSM, nDSM
DEM, DTM have different definitions in different countries.In Russian (по-русски) ЦМР, ЦМП
DEM & DTM - bare earth terrain. DSM include tree canopy & buildings.nDSM = DSM - DTM
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PHOTOMOD. Different models (depending on algorithm)
Automatic DSM (old cross-correlation algorithm) with filtering buildings and trees
Automatic DSM (old cross-correlation algorithm)
3D semi-automatic model (with manual stereo vectorization)
Different models for Novokuznetsk city GeoEye-1 stereopair (GSD 0.5m)
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Local algorithms of DTM creation
Memory efficient Fast Subpixel accuracy in
“smooth” regions Problems with periodic
structures and poorly textured regions
Big problem with discontinuities on images
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Global algorithms of DSM creation
Global energy minimization Take into account discontinuities and
hidden surfaces Not memory efficient Still require filtering and smoothing in
the end of algorithm
E = E(data) + E(smooth)
Semi Global Matching (SGM) Graph-cuts Simple Tree Iterative- deformation method
(RACURS)
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Local vs Global method
SGM andIterative deformation methods
CrossCorrelation
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PHOTOMOD: iterative deformation method (IDM)
All images are taken into account simultaneously
Memory efficient
Image pyramid hierarchy is used for speed and reliability
Image resection is used to calculate occlusions
Still requires filtering and smoothing on the final step
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height approximation levels
1-st image 2-nd image
DSM
orthophoto
Point with unknown height
PHOTOMOD: iterative deformation method (IDM)
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IDM vs SGM
We used SURE (Institute for Photogrammetry (IfP), University of Stuttgart) as SGM example
SGM is faster (20-30%) on the local computer
IDM is faster in the network environment (parallel computing based on images + dsm levels and area splitting)
IDM does not need epipolar geometry
IDM uses all images simultaneously
IDM uses different strategies based on the DSM guess
IDM uses elements of pattern recognition for different height approximations
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PHOTOMOD 6.0 - User interface
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IDM: GeoEye example
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IDM: GeoEye example
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IDM: WorldView 1 example
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IDM: WorldView 1 example
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IDM: UltraCam example
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IDM: UltraCam example
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IDM: UltraCam example
18www.racurs.ru
IDM: DMC example (Munich block)
19www.racurs.ru
IDM: DMC example
20www.racurs.ru
Thank you