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Centre Spatial de Liège Institut Montefiore

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Presentation on theme: "Centre Spatial de Liège Institut Montefiore"— Presentation transcript:

1 GEMITOR GEoréférencement Multimodal d’Images Tridimensionnelles Optiques et Radar
Centre Spatial de Liège Institut Montefiore Université de Liège, Belgium MULTIMODAL GEOREFERENCING of 3D VHR OPTICAL and X-BAND SAR IMAGERY Antonella Belmonte

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

3 Context

4 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

5 GEMITOR GEoréférencement Multimodal d’Images Tridimensionnelles Optiques et Radar
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)

6 Issues

7 C-band vs. X-band Airborne vs. spaceborne
Standard resolution X-band Spaceborne Very High Resolution X-band Airborne Very High Resolution

8 Simulated data range 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 azimuth

9 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 ~ Km ~ Km MINIMUN RANGE ~ 840 Km ~ 3,9 Km PULSE REPETITION FREQUENCY ~ 1679,79 Hz ~ 148,148 Hz

10 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

11 Phenomenology (review)

12 Shadowing example range Due to the low depression angle, in RAMSES images, shadowing is predominant with respect to layover and foreshortening. SHADOW SHADOW azimuth SHADOW

13 Buildings example range Buildings azimuth

14 VHR details At VHR one easily observes: range Vehicle Parcel limits
Different crops azimuth At VHR one easily observes: topographical limits parcel limits buildings vehicles Buildings Road

15 Technical approach

16 InSAR testing Testing of CSL InSAR processor using RAMSES interferometric data set Slave image already coregistered ==> no testing of the coregistration module Same Doppler centroid ==> no azimuth filtering

17 Pixel averaging 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).

18 Results

19 InSAR processing first results
range RAMSES HEADER slave parameters Fos202208_MS_rad_0.dat # Mode interferometrique : Compensation_IF= distance_doppler Retard_apres_demod_hard= s Baseline_x= m Baseline_y= m Baseline_z= m azimuth If we force Baseline_y= 0.0 m Baseline_z= 0.0 m, the processor gives the following interferogram. We thus suppose that the slave image is already compensated for “orbital” phase wrong « orbital » phase compensation correct « orbital » phase compensation

20 InSAR processing test samples – 1X1 pixel averaging
Amplitude Coherence Interferogram Phase Unwrapping

21 Simulated CosmoSkyMed data
Unwrapped phase test Simulated CosmoSkyMed data RAMSES data Pixel averaging 3x3 Pixel averaging 1x1 Pixel averaging 5x5 Pixel averaging 1x1 Pixel averaging 3x3 Pixel averaging 5x5

22 Amplitude SAR image Optical image Unwrapped phase
At high resolution, the uniform pixels (containing scatterers sharing the same backscattering properties) are more numerous and give a phase response, peculiar to their own physical properties, in addition to the optical path component which is used to compute local heights. Consequently, backscattering characteristic variation appears from a pixel to an adjacent one in the unwrapping phase surface (particularly in the urban area). Unwrapped phase

23 45 deg. -rotated master image example
Interpolation test (1) 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 45 deg. -rotated master image example

24 Interpolation test (2) We regenerate an interferogram from rotated image samples non-rotated interferogram 45 deg.-rotated interferogram

25 180 deg.-rotated interferogram
Interpolation test (3) Master and slave images were rotated 45 deg. successively up to 180 deg. to generate the corresponding interferogram ==> Interpolator used 4 times successively 180 deg.-rotated interferogram

26 Interferogram differences
Interpolation test (4) The obtained interferogram was flipped and compared to the original one No visible trends Histogram of the differences well centerd on a null phase ==> The CSL interpolator is convenient for VHR SAR Data Interferogram differences Histogram of differences

27 Current InSAR processor 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

28 Conclusions

29 The CSL InSAR processor is a good basis for the GEMITOR project since:
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

30 Future work

31 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

32 Thank you for your attention!


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