17th DLR-CNES Workshop on Information Extraction and Scene Understanding for Meter Resolution Images

GEMITOR GEoréférencement Multimodal d’Images Tridimensionnelles Optiques et

Radar MULTIMODAL GEOREFERENCING of

3D VHR OPTICAL and X-BAND SAR IMAGERY

Antonella Belmonteabelmonte@ulg.ac.be

Centre Spatial de LiègeInstitut Montefiore

Université de Liège, Belgium

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OUTLINE

Context Issues Phenomenology (review) Technological approach Results Conclusions Future work

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Context

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ORFEO Optical and Radar Federated Earth

Observation

Very High resolution Optical (PLEIADES) and RADAR (Cosmo-Skymed) modalities possibly acquired simultaneously

Strong need for optical and radar modalities fusion at pixel level to take full advantage of the ORFEO opportunity

Need for 3D information extraction (InSAR) for georeferencing the radar modality

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To investigate the limitations of current InSAR techniques

To modify/adapt existing algorithms to VHR peculiarities

To test algorithms on simulated Cosmo-SkyMed data

To georeference visible and SAR images in common reference frame

To fuse SAR and optical VHR images at the pixel level

To develop 3D visualization tools (virtual reality)

GEMITORGEoréférencement Multimodal d’Images Tridimensionnelles

Optiques et Radar

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Issues

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C-band vs. X-bandAirborne vs. spaceborne

•C-band•Spaceborne•Standard resolution

•X-band•Airborne•Very High Resolution

•X-band•Spaceborne•Very High Resolution

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Simulated data

Tests performed on simulated CosmoSkyMed RAMSES data set:

Airborne SAR interferometric data set (RAMSES = Radar Aéroporté Multi-Spectral d’ Etude de Signatures)

VHR: • resolution cell azimuth: 0.55 m• resolution cell slant range: 0.49 m

Site: Baux de Provence Single polarization (VV) Single-pass

azim

uth

range

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Geometrical differences between spaceborne and airborne SAR

acquisitions

Spaceborne SAR

(ERS)Airborne SAR

(RAMSES)SWATH 25 – 500 Km 10 – 100 Km

INCIDENTCE ANGLE wrt NORMAL

20 – 45 deg. 30 – 85 deg.

DISTANCE SENSOR-CENTER OF THE EARTH

~ 7 150 Km ~ 6 373 Km

MINIMUN RANGE ~ 840 Km ~ 3,9 KmPULSE

REPETITION FREQUENCY ~ 1679,79 Hz ~ 148,148 Hz

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VHR images specific characteristics

Some RAMSES images specific characteristics may lead to InSAR processing difficulties and require some specific algorithmic design: Shadowing Specific backscattering & brightness Man-made features

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Phenomenology (review)

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Shadowing example

Due to the low depression angle, in RAMSES images, shadowing is predominant with respect to layover and foreshortening.

azim

uth

range

SHADOW

SHADOW

SHADOW

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Buildings example

Buildingsrange

azim

uth

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VHR details At VHR one easily observes:At VHR one easily observes:range

azim

uth

Road

Parcel limits

Different crops

Vehicle

Buildings

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Technical approach

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Slave image already coregistered ==> no testing of the coregistration module Same Doppler centroid ==> no azimuth filtering

InSAR testing Testing of CSL InSAR processor using RAMSES interferometric data set

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The testing study of the InSAR processor was done, using three different pixel averaging (5x5, 3x3, 1x1) when generating the interferometric products.

Final goal is to work with the image at full resolution pixel 1x1 (RAMSES 0,55 x 0,49m).

Pixel averaging

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Results

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InSAR processing first results

Fos202208_MS_rad_0.dat# Mode interferometrique : Compensation_IF= distance_doppler Retard_apres_demod_hard= 0.000000 s Baseline_x= 0.000000 m Baseline_y= -0.1017500m Baseline_z= -0.6046000 m

RAMSES HEADER slave parameters

wrong « orbital »phase compensation

correct « orbital »phase compensation

azim

uth

range

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InSAR processing test samples – 1X1 pixel averaging

Amplitude Coherence Interferogram

Phase Unwrapping

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Simulated CosmoSkyMed data

RAMSES data

Pixel averaging 1x1

Pixel averaging 1x1

Pixel averaging 3x3 Pixel averaging

5x5

Pixel averaging 3x3

Pixel averaging 5x5

Unwrapped phase test

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Optical image

Amplitude SAR image

Unwrapped phase

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CSL interpolator is based on Chirp-Z transform

It allows applying any affine transform to complex data:

To test the interpolator, we apply a 45 deg. rotation to both the master and the slave images

Interpolation test (1)

45 deg. -rotated master image example

zzz

xxx

CzBxAzCzBxAx

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112

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We regenerate an interferogram from rotated image samples

Interpolation test (2)

45 deg.-rotated interferogramnon-rotated interferogram

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Master and slave images were rotated 45 deg. successively up to 180 deg. to generate the corresponding interferogram

==> Interpolator used 4 times successively

Interpolation test (3)

180 deg.-rotated interferogram

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Interpolation test (4)

Interferogram differences Histogram of differences

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Current InSAR processor limitations

Limitations : The phase unwrapping module works well at full

resolution (1x1). but other tests will be performed on more complex areas (i.e. urban area)

Improvements : To work at multiple resolutions To improve the residues connection algorithm

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Conclusions

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Geometrical differences between airborne and spaceborne acquisitions must be taken into account in future developments

The CSL InSAR processor is a good basis for the GEMITOR project since: The Chirp-Z transform based interpolator is suitable for

handling VHR SAR data Phase unwrapping must be adapted to VHR peculiarities

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Future work

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To test (and adapt if required) the SAR georeferencing routines

To study optical and radar modality complementary

To bring the optical and SAR modality into the same geographical reference frame at pixel level

To visualize the fusion products and all 3D information in 3D stereo

Thank you for your attention!Thank you for your attention!