1 from imagery to map: digital photogrammetric technologies 14 th international scientific and...

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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