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DEM REGISTRATION, ALIGNMENT AND EVALUATION FOR SAR 
INTERFEROMETRY 
Zhengxiao Li a , James Bethel b 
a ERDAS, Inc. (Leica Geosystems Geospatial Imaging), 5051 Peachtree Comers Circle, Norcross, Georgia 30092, USA 
- tonybest@gmail.com 
b Purdue University, School of Civil Engineering, 550 Stadium Mall Drive, West Lafayette, IN 47907-2051, USA - 
bethel@purdue. edu 
KEY WORDS: DEM, Accuracy assessment, SAR Interferometry, Digital elevation models, Registration, Image matching, 
Transformation, Parameters 
ABSTRACT: 
To generate an accurate digital elevation model (DEM), Interferometric Synthetic Aperture Radar (InSAR) requires precise orbit data 
and baseline information, which are not always available. An alternative approach is to apply quality ground control points (GCPs) 
into the InSAR processing. However, locating high quality GCPs can also be difficult task, due to the low spatial resolution and 
radiometric response of synthetic aperture radar (SAR) images. This paper presents a method to register and align an InSAR DEM, 
generated from SAR images without precise orbit or baseline information and without GCPs, to an existing coarse reference DEM for 
refinement. The results showed this method achieves a comparable or even better accuracy than applying GCPs into InSAR processing. 
It was also found that the existing DEM with lower resolution than the InSAR DEM could be a good reference for this registration and 
alignment, i.e. refinement. ERS1/2 tandem SAR image pairs were used for 16-meter (post spacing) InSAR DEM generation. Both 
InSAR processing with and without applying GCPs were conducted for comparison purposes. The InSAR DEM was registered and 
aligned to SRTM 3 Arc Second data, a global reference DEM. The “truth” DEM used for accuracy evaluation is a higher accuracy 
DEM from aerial imagery with post spacing of 1.5 meters and vertical accuracy of 1.8 meters. 
1. INTRODUCTION 
In order to generate an accurate digital elevation model (DEM) 
through Interferometric Synthetic Aperture Radar (InSAR) 
processing, by conventional methods, precise orbit and baseline 
data are required for processing. Unfortunately, these are not 
always available. An alternative approach is to apply ground 
control points (GCPs), which are used to adjust and refine orbit 
and baseline data (Zebker et al., 1994), or to refine the final 
InSAR DEM externally (Ge et al., 2004). However, due to the 
low spatial resolution and radiometric response of synthetic 
aperture radar (SAR) images, locating high quality GCPs can 
also be difficult task (Sowter et al., 2006; Toutin et al., 1998). 
Another method was developed to refine an InSAR DEM that 
does not require precise orbit and baseline data or accurate 
GCPs. The approach involves registering and aligning the new 
InSAR DEM to an existing coarse reference DEM. No orbit or 
baseline adjustment is needed. Coverage, currency, or accuracy 
issues may prohibit direct use of these existing reference DEMs, 
but they may be good enough to align and register the InSAR 
DEM. They could also reduce the InSAR processed DEM 
errors caused by the lack of precise orbit and baseline 
knowledge, and lack of accurate GCPs. 
Registration is also called marching, which is to search for 
corresponding control points on InSAR DEM and reference 
DEM. Those corresponding control points are then used for 
deriving seven-parameter transformation equations by least 
squares. Through the seven-parameter transformation equations, 
InSAR DEM is converted and aligned to reference DEM. 
processing. It is also found that an existing DEM with lower 
spatial resolution than the InSAR DEM can be used as a 
reference for the registration and alignment, i.e. refinement. 
In this research, two pairs of ERS1/2 tandem SAR images were 
used for 16-meter (post spacing) InSAR DEM generation. 
InSAR processing with and without applying GCPs was 
performed for comparison purposes. The InSAR DEM was 
registered and aligned to SRTM (Shuttle Radar Topography 
Mission) 3 Arc Second data, a global reference DEM. The 
“truth” DEM used for accuracy evaluation is a higher accuracy 
DEM from aerial imagery with post spacing of 1.5 meters and 
vertical accuracy of 1.8 meters. 
2. METHODOLOGY AND ALGORITHM 
Due to the inaccurate orbit and baseline information, the InSAR 
DEM distortion is mostly vertical tilt and offset, horizontal 
offset, and scaling or stretch. The approach of registration and 
alignment is to find the geometric relation between the newly 
developed InSAR DEM and the existing coarse DEM, and to 
correct the InSAR DEM. The existing coarse DEM may have 
the lower resolution, but it could be good to reduce the 
systematic bias error of the InSAR DEM with higher resolution, 
horizontally and vertically. 
Conventional image registration can be envisioned as a 2.5 
dimensional problem. Nearly aligned DEMs may also be 
handled as a 2.5 dimensional problem, whereas significant 
misalignments may require handling as a full three dimensional 
problem. A three dimensional (3D) model can be approached as 
a simultaneous solution or as a series of lower order 
The results show that this method achieves a comparable or 
even better accuracy than incorporating GCPs into the InSAR