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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
However, on longer time intervals, interferometry is no more
adequate.
On the other hand, precise sub-pixel correlation techniques
have already been used (Vadon, 2000), but not yet in the field
of glaciers displacement. The following study is an ongoing
work of OMP and CNES, using high resolution (SPOTS
THR) image correlation for displacement measurement.
2 DISPLACEMENT FIELD
MEASUREMENT BY CORRELATION:
METHODOLOGY
2.1 Introduction
The general principle of offset computation by correlation is
the following: around every reference image point, for which
one wants to compute the local offset with a secondary
image, a so-called rectangular “vignette” is constituted,
centered on the reference point. Having a rough knowledge
of the local offset, we can center the search on the secondary
image around the estimated position. We iteratively build a
small vignette on the secondary image, which has the same
size as the primary one, and which travels through an area
called "research area" (Figure 1). The size of this research
area is related to the uncertainty on the position in the
secondary image.
Cr C,=Cr+AC
T 1
| i
| Vignette 1 '
1 T i
^ i | Vignette 2
leq i
LALa4*AL Cs
(Ls C) 13 que
: Research area
Primary image
Secondary image
Figure 1: Correlation windows principle
(L and C refer to line and column in the images)
First, correlation rates are computed for every vignette
position in the research area. The best correlation
corresponds to the position in. the research area of the
secondary image that maximizes the radiometric resemblance
between the two vignettes.
For sub-pixel search, the principle is similar, except that the
second image is re-sampled in the vicinity of the position
computed at the previous step. Second loop is performed at
*-0.5 pixel in line and column, third loop at +-0.25 pixel
around the previous position, and so on. Process stops when
the required localization accuracy is reached.
This principle is general to all offset computation between
images. Specific to glaciers is the fact that the surrounding
slopes are stable, whereas the glaciers themselves have
moved. Therefore, it is important that the software allows a
variable search window size: very small research area on the
glacier surroundings, and large one on the glacier itself. As a
matter of fact, research area must always be as small as
possible, because secondary correlation picks are one of the
limiting factors of the method.
The conditions for an accurate offset computation are:
831
* . Well sampled, aliasing free images. This is the case for
SPOT5 THR images, thanks to its two quincunx arrays
of detectors (Latry, 1995).
* Similar radiometry: this implies minimum time delay
between the two acquisitions.
+ Similar geometry: this implies acquiring images from
the same viewpoint or at least as similar as possible
viewpoints (similar incidence angles). In the case of
SPOTS, the best configuration is a time interval multiple
of 26 days, the orbital cycle.
2.2 Geometrical model
Before computing the local offsets between reference and
secondary images, it is important to resample the secondary
image, in order to make it as close as possible geometrically
to the reference one. Correlation assumes a local radiometric
linear relation between the two vignettes (y = ax + b, where y
is the secondary radiometry and x the reference radiometry),
and this relation can only be true if the geometry of the
secondary image is very close to the one of the reference.
This resampling process requires an accurate geometrical
model. Starting with initial system variables, ephemeris and
attitude data, provided with the images, geometrical
modeling is achieved by automatic bundle block adjustment.
We obtain a refined geometrical model (refined attitude -
biases and first order derivatives).
The process requires a Digital Elevation Model (DEM) of the
region. At this stage, it is not necessary to have a very good
quality DEM, because the process is global. Typically, a
DTED level 1 DEM is sufficient. The process of relative
bundle block adjustment does not require ground control
points. However, in our study area, we made two different
computations, with and without ground control points
(GCPs) in other words with absolute and relative
geometrical modeling.
The inputs to the bundle block adjustment are homologous
points, issued from a first correlation between the two raw
images. The process models the impact of attitude (roll, pitch
and yaw) biases and derivatives, and tries to minimize the
residuals on the non-glacier areas. This method, which uses
the physical attitude models, is better than the classical one,
which tries to make a polynomial fit of the residual on the
offset grids themselves (Figures 3 and 4).
At the end of this first step, we are able to resample the
secondary image to the geometry of the reference one, in
such a way that the non-glaciated areas are superposable.
Therefore, all measurements done over the glaciers are now
absolute: they represent the movement only, without any
orbital and attitude residual.
2.3 Offsets computation by correlation
Glaciers, at least over one summer season, have proved to
correlate quite well: their texture is adequate at the scale we
are working (2.5m resolution), even when considering the
fact that they partially melt in surface. However, one must be
careful with year to year correlation: crevasses are stationary,
and the measured displacements could be found to be almost
null over one year!
Glaciers surface might have moved a lot during the
acquisition interval. Dependant of the image resolution, the
