points σ =
4 cm for X, Y and Z. The considered shift and drift parameters
measurements, IMU misalignment and s parameters for each camera.
Self-calibration led to significantly impr Trimble Inpho software allows applying tw
self-calibration parameters: the 12 so-called Ebner, 1976 and the 44 so-called Grün
1979. Figure 4 shows the averaged r coordinates for the Nadir image derived fro
without self-calibration. The mayor systema compensated by applying self-calibration w
The set of 12 parameters did not result in sat accuracy.
Figure 4. Calculated distortion grid for From 12 independent check points, RMS ob
of 3.2 cm in X, 4.5 cm in Y and 6.6 cm i Figure 5 shows the graphical representat
control and check point residuals.
Figure 5. Horizontal left and vertical ground control points triangles and check p
This well characterized block-configuration preferred to generate preliminary dense
subsequent
textured meshes
using Smart3DContextCapture software package A
4. RADIOMETRIC CALIBR
The availability of remote sensing data, eith manned and unmanned airborne platforms, i
more due to their useful applications in a wi Airborne photogrammetric systems are abl
resolution imagery over large areas in a tim increasingly used for different application
monitoring and environmental conditions e adjustment settings
ers of the GNSS self-calibration 44
proved results. The two different sets of
lled Ebner parameters ün parameters Grün,
residuals of image from block adjustment
matic effects could be with 44 parameters.
satisfying object point
for Nadir camera object point residuals
in Z were obtained. tation of the ground
l right residuals of k points circles
ion has been the one se point clouds and
ing the
Bentley e Acute3d.
RATION
ither from satellites or is growing more and
wide variety of fields. able to provide high-
imely manner, being ons such as land-use
ns assessment. As a consequence, as well as geom
integrity becomes a key task o exploitation of photogrammetric
increasingly emphasizing the ro calibration through the incorpora
involving radiometric calibration o step basically translates the recorde
physical information radiance us pixel level that are estimated b
measurements. As a matter of sensor manufacturers, usually d
geometrically high-performance sy absolute calibration of their sensors
provide the constant values to cust a workflow to generate radio
automatically. The aim of this section is to asses
calibration workflow included in software package for the RCD30 P
operated at ICGC. To evaluate th ICGC has developed a procedur
acquisition of RCD30 oblique ima hyperspectral sensor.
The AISA Eagle II, which is reg calibrated once a year by SPECI
facilities after calibration and systematic validation of its radiom
This protocol follows these steps:
1. AISA Eagle II sensor is
the Integrating Sphere 2.
Acquisitions of approx. of dark lines are carried o
3. Image is radiometricall
pixel calibration coefficie 4.
Radiance information of averaged being the ima
the sphere, only the centr illuminated.
5. Radiance is compared
curve of the Integrating National Physical Lab
shows the resulting comp
Figure 6. Absolute radiometric ca validation at ICGC
metric precision, radiometric of data processing for the
ic data. The ICGC has been role of absolute radiometric
oration of innovative products n of data into its portfolio. This
rded digital numbers DNs into using correction coefficients at
by integrating sphere in-lab f fact, even photogrammetric
devoted to the design of systems, take great care of the
ors. Nowadays, they are able to ustomers and, at best, to include
iometrically-corrected images sess the quality of the absolute
in the image post-processing 0 Penta Oblique camera model
the quality of these measures, dure based on a simultaneous
magery and the AISA Eagle II egularly operated by ICGC, is
ECIM. Once it returns to our d maintenance operations, a
ometric precision is carried out. is placed about 20 cm far from
x. 500 lines and 5 milliseconds d out.
ally-corrected using pixel-by- icients.
of illuminated pixels is time- mage taken at a distance from
ntral part of the field of view is d with the spectral radiation
ting Sphere provided by NPL aboratory
in UK. Figure 6 mparison.
calibration of AISA Eagle II
This contribution has been peer-reviewed. doi:10.5194isprsarchives-XLI-B3-99-2016
101
The validation procedure demonstrates the reliability of the AISA absolute calibration as a reference to assess the
radiometric performance of RCD30 images. With this aim, the 126 useful AISA spectral bands T2 block-configuration have
been integrated according to RCD30 spectral filters leading to 4-bands imagery that can be used for the assessment in a
consistent manner. The evaluation has been carried out for each channel separately
over seven terrain samples representing a heterogeneous set of land covers e.g. forest, field, asphalt, bare soil, etc.. Thus, a
difference image has been calculated from both AISA and RCD30 acquisitions. The statistics computed for each sample
show an averaged difference of 22.91 Wm
2
sr
-1
µm between blue band calibrated images. Moreover, the averaged difference
values found in green, red and near infrared channels are 36.33, 59.66 and 37.04 Wm
2
sr
-1
µm respectively. Figures 7, 8, 9 and 10 show the mean values obtained from the histogram of each
sample in both AISA and RCD30 calibrated images. Figures 7,8,9,10. Histogram mean values computed for each
sample and each band. Y axis represents Radiance
As a final summary of the previous measures, Table 1 shows the relative error of the RCD30 absolute calibration.
Blue Green
Red Near
Infrared Relative
error 2.44
3.26 4.57
2.1 Table 1. Relative error of the RCD30 absolute calibration
5. IMAGE RESOLUTION
