(Schenk, T. et al., 2003). Technical specifications are listed in
Table 3.
Lens Petzval f/3.5 T 3.8
Focal Length 609.602mm (24.0 in)
Scan Angle 70 deg +/- 35 deg from track)
Field of View | 5.12 deg (along track)
Usable 29.323" X 2.147"
Format
Shutter Focal Plane
Slit Widths Variable-- from 0.17 in to 0.30 in
1. 70mm Wide
2. 8,000 ft per recoverable sub-system
(part 1 or 2 of a mission) for each camera
Film Load 3. 16,000 ft per recoverable sub-system
4. 16,000 ft per camera per mission
5. 32,000 ft total load for both cameras
for a mission (part 1 and 2)
End Lap 7.6 percent;
Image Motion | Camera nods proportional to
Compensation | velocity/height (V/H) ratio
Stereo Angle 30.46 degrees
Filter Variable -2 position commandable
Film Type 3404, Estar Base
Table 4. Corona panoramic camera specifications [2]
In this study, Corona image acquired on 16/09/1964 by KH-4A
panoramic forward camera was used. The pass was descending
from north to south. Panoramic cameras are mounted in the
photographic vehicle at a 15? angle from the vertical, thus
forming a 30? convergence angle. The cameras are designated as
forward-looking and after-looking. Resolution is about 3 m.
Because film transparencies tend to have higher spatial
resolutions and a greater range of gray values than paper prints,
they are the preferred source material when converting aerial
photographs to digital images. Corona image was scanned with
a photogrammetric scanner DSW700 with optimal 10 um
(2540dpi) optical resolution, with attention to radiometric
ground detail.
For the Corona image rectification, 19 points were used.
Naturally, the homogeneous distribution of the control points
on the image has been taken in to account. The ratio between
the altitude of Corona satellite (about 185,200 m) and the
maximum exaggeration of elevation difference on the study area
(30 m) was calculated and it was seen that the relief
displacements due to elevation difference, can be ignored.
Therefore, the study area was assumed to be flat and the
polynomial rectification methods were utilized. For best
rectification results, Rubber Sheeting method was applied
(Byram, B. et al, 2004).
In order to perform the triangle-based rectification, it is
necessary to triangulate the control points into a mesh of
triangles. Delaunay triangulation is most widely used and is
adopted because of the smaller angle variations of the resulting
triangles. This triangle based method is appealing because it
breaks the entire region into smaller subsets. If the geometric
problem of the entire region is very complicated, the geometry
of each subset can be much simpler and modeled through
simple transformation. For each triangle, the polynomials can
be used as the general transformation form between source and
destination systems.
The most popular method to register images (image to image) is
Rubber Sheeting. In this case, a low order 2D polynomial is
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
fitted through data points and control points in order to
transform Corona image to photogrammetric image.
Figure 5. Small portion of Corona image depicting study area
The polynomial coefficients are then used to transform non-
control points. The simplest transformation in this scheme is an
affine transformation (Schenk, T. et al, 2003).
X 1.5327 meters
Y 1.2618 meters
TOTAL 1.9473 meters
Table 6. Check Point Error
Precision of the Rubber Sheeting method was performed by
measuring 24 control and 15 check points with 1.95 m accuracy
(Table 4).
3.4 SPOT HRY image processing
For this study have been used a SPOT-3-HRV (09/07/1994)
multispectral image — 20m resolution and a panchromatic image
- 10 m resolution taken over Bucharest. There are different
techniques to combine SPOT satellite images with two different
ground resolutions. Using various image processing methods,
including enhancement techniques, a good quality image
suitable for multiple applications can be easily achieved.
Atmospheric correction using only a first order additive haze
model was applied to the multispectral bands. The cut-off points
were derived from the histogram showing the minimum value of
each band. The estimated haze contribution to the signal is
subtracted from the photon count value in each band for all
elements in the numerical image (Essadiki, M, 2004).
The panchromatic and multispectral images in this study were
acquired on the same orbit in the same day. For this reason, an
affine transformation was used. The specific error model was
derived from: the position of actual grid of scene elements (x, y)
and the indices in the numerical matrix: (x, y) — f (row,
column), the position of grid cells in the ideal grid (u,v) and the
corresponding indices: (u, v) = g (row’, column’). For
resampling the 20 m multispectral data into 10 m scene
elements, a file containing twenty-four ground control point
coordinates was needed. This was achieved by identifying sets
