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INCREASING GEOMETRIC ACCURACY OF DMC’S VIRTUAL IMAGES
M. Madani, I. Shkolnikov
Intergraph Corporation, Alabama, USA (mostafa.madani@intergraph.com)
Commission I, WG 1/1
KEY WORDS: Digital Aerial Cameras, Camera Calibration, Bundle Adjustment, Self-calibration, Geometric Correction, Accuracy
ABSTRACT:
In the last two to three years, there have been a number of investigations into the geometric accuracy of large format digital cameras,
particularly for large scale and engineering application. Geometric calibration of a silicon pizza image from a multi-camera platform
seems to be the most challenging issue. The main problems in this effort include a combined camera lens and imaging raster frame
calibration at the same time and a multi-camera platform exterior orientation (EO) calibration. Not corrected systematic image
errors reduce the image accuracy and can propagate unfavorably into object space during aerial triangulation. This leads to a lower
vertical accuracy of determined object points. In this paper, two different methods are used to remove or model the remaining
systematic errors of the DMC (Intergraph Digital Mapping Camera) virtual images: the first method tries to remove systematic
image errors by a posteriori interpolation treatment of the image residuals from bundle adjustments of test field blocks. Correction
grids are then used as inputs in the DMC Post-processing software to generate virtual images or used in the real-time math model of
the ImageStation products. The second method tries to describe the systematic errors using “proper” sets of additional parameters in
self-calibration bundle adjustments. These methods were applied on the several DMC test blocks of varying GSDs (Ground
Sampling Distances). This study showed that the magnitude of the remaining systematic errors of the image residuals is constant and
ranges between 0.5pm and 3pm. Furthermore, these methods were able to increase the vertical accuracy of the object points by a
factor 2 to 4 times.
1. INTRODUCTION
Intergraph’s Digital Mapping Camera (DMC), introduced into
the market in early 2003, is based on Charge Coupled Device
(CCD) frame (matrix) sensor and provides a very high interior
geometric stability. The camera was designed to perform under
various light conditions with a wide range of exposure times.
Features such as electronic Forward Motion Compensation
(FMC) and 12-bit per pixel radiometric resolution for each of
the panchromatic and color channel camera sensors provide the
capabilities of operating even under less than favorable flight
conditions. The DMC System allows you to produce small-
scale or large-scale images with ground resolutions of fewer
than two inches. The results are images with greatly improved
radiometric resolution and increased accuracy of
photogrammetric measurements.
The DMC itself is a digital aerial camera consisting of 8 sensors:
4 panchromatic sensors and 4 multi-spectral sensors. The multi-
spectral sensors are 3k x 2k in size, with one sensor capturing
red data, one capturing blue data, one capturing green data, and
one capturing near-infrared data. The four panchromatic sensors
each capture one image of a particular area (7k x 4k), which
slightly overlap one another and are used to produce one large
mosaicked image, 7680 x 13824 in size. From the image data
captured by the camera, you can produce a variety of output
types using the Postprocessing software.
The image data that the camera captures is stored on the Solid
State Disk (SSD) which is attached to the camera system. This
storage unit can easily be detached from the DMC and replaced
by an empty one during the photo flight.
Figure 1. DMC with gyro stabilized mount and SSD
The DMC Postprocessing Software (PPS) is used for producing
virtual images from the raw image data. Postprocessing is
completed in two steps: radiometric processing and then
geometric processing. Radiometric postprocessing compensates
for the effects of defect pixels, the individual sensitivity of each
single CCD pixel, vignetting, the influence of aperture, and the
filter influence (for correction on multi-spectral images). The
intermediate images, generated from the radiometric processing,
are then geometrically corrected for lens distortion using the
laboratory calibration parameters of the individual camera
heads and are subsequently combined to form the image
composite (Dòrstel, 2003).
Thousands of the DMC projects have been successfully flown
by different customers all over the world. All these DMC
projects achieved the required accuracy standards for different