Automated Registration of Synthetic Aperture Radar Imagery to LIDAR

transcript

Automated Registration of Synthetic Aperture Radar

Imagery to LIDAR

Mark Pritt, PhDLockheed Martin

Gaithersburg, Marylandmark.pritt@lmco.com

Kevin LaTouretteLockheed MartinGoodyear, Arizonakevin.j.latourette@lmco.com

IGARSS 2011, Vancouver, CanadaJuly 24-29, 2011

Problem: SAR Image Registration

· Registration of SAR and optical imagery is difficult. Features appear different. Different viewpoints and illumination conditions cause difficulties:

SAR layover does not match optical foreshortening. Shadows do not match.

· Conventional techniques rely on linear features. But these features can be rare and noisy in SAR imagery.

SAR image

MSI image

Solution

· Our solution is image registration to a high-resolution digital elevation model (DEM): A DEM post spacing of 1 or 2 meters yields good results. It also works with coarser post spacing.

· Works with terrain data derived from many sources: LIDAR: BuckEye, ALIRT, Commercial Stereo Photogrammetry: Socet Set® DSM SAR: Stereo and Interferometry USGS DEMs

· Create a predicted image from the DEM, illumination conditions and sensor model estimate.

· Register the predicted and the actual images.· Refine the sensor model.

Methods

SAR ImagePredicted SAR Image

· The same approach works for SAR and optical sensors. Projection into the imaging plane is similar. Layover in SAR images is similar to occlusion in optical images. Radar shadow is similar to optical shadow.

Methods (cont)

SAR Sensor

Image Plane

SceneLayover Shadow SceneOcclusion

Optical Sensor

Image Plane

Shadow

Methods (cont)

· To register SAR and optical images, use the DEM as the “bridge”. Generate a predicted “DEM” image for each SAR and optical

image. Register the predicted images to the actual images. This neatly bypasses the problem of direct SAR-optical registration.

SAR Image DEM MSI Image

Example 1: SAR-LIDAR Registration

COSMO-SkyMed SAR Image of Mosul, Iraq BuckEye LIDAR DEM

Area: 100 km2

21,000 x 20,000 pixels

Post Spacing: 1 meterAbsolute Accuracy: 1.5 m (CE90)

Results

COSMO-SkyMed SAR Image

Results (cont)

Predicted SAR Image from DEM and Estimated SAR Camera Model

Flicker with previous slide

Results (cont)

Normalized Cross-Correlation Image Between Predicted and Actual Images

Results: Zoom

COSMO-SkyMed SAR ImageNote the

SAR layover and shadow

Zoom (cont)

Predicted SAR Image from DEM

Note the SAR layover and shadow

Zoom (cont)

Cross Correlation

Registration Accuracy

NCC Registration Tie Points

After least-squares fit to shift-only registration function with RANSAC outlier removal, 4572 tie points remained.

Best shift:Δx = 16.76mΔy = 4.27m

Registration Accuracy (cont)

Error Propagation

Statistic x y

Mean Residual 0 pixels 0 pixels

Sigma Residual 0.948 pixels 0.981 pixels

RMSE 1.364 pixels

Circular ErrorPropagated to DEM 1.48 m (CE90)

Circular ErrorPropagated to Ground 2.1 m (CE90)

This includes the geospatial errors in the DEM and the registration.

CE90 = circular error 90%

Results: SAR-MSI RegistrationSAR Image: COSMO-SkyMed, Date: Oct 2008, GSD: 1 m

SAR-MSI Registration (cont)MSI Image: IKONOS, Date: Oct 2010, GSD: 2.2 m

SAR-MSI Registration (cont)SAR Image: COSMO-SkyMed, Date: Oct 2008, GSD: 1 m

Example 2: SAR-MSI-LIDAR Fusion

Waterton, Colorado

IkonosMSI

COSMO- SkyMed

BuckEyeLIDAR DEM

BuckEye Lidar: March 2003 (4.1 x 5.2 km, 0.75-m post spacing)Ikonos: July 9, 2001 (1-m GSD). COSMO SkyMed SAR: Oct 31, 2008 (0.5-m GSD)

Results: EO Image Draped Over DEM

Note alignmentof features

Results: SAR Image Draped Over DEM

Results: MSI Image Draped Over DEM

Results: Fly-Through

Click picture above to play movie

Conclusion

· We have introduced a new method for registering SAR images with other sensor data: LIDAR, Digital Elevation Models, Optical Images, MSI

· It works by image registration to a high-resolution DEM. It does this by generating a predicted image from the DEM and

sensor model estimate. It then registers the predicted and actual images and refines the

sensor model estimate.· Accuracy: 1-2 m CE90· Our approach also extends to the case where no DEM

is available: DEM can be generated from stereo EO or interferometric SAR.

Conclusion (cont.)

· For an extension to Video Geo-registration: Pritt, M & LaTourette, K., Stabilization and Georegistration of Aerial Video Over

Mountain Terrain by Means of LIDAR. FR1.T08.4

Automated Registration of Synthetic Aperture Radar Imagery to LIDAR

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