The research group with the responsibility of the STereo Camera (STC) for the ESA BepiColombo mission to Mercury, has realized an innovative and compact camera design in which the light collected independently by two optical channels at ±20° with respect to the nadir direction converges on unique bidimensional detector. STC will provide the 3Dmapping of Mercury surface, acquiring images from two different perspectives. A stereo validation setup has been developed in order to give a much greater confidence to the novel instrument design and to get an on ground verification of the actual accuracies in obtaining elevation information from stereo pairs. A series of stereo-pairs of an anorthosite stone sample (good analogue of the hermean surface) and of a modelled piece of concrete, acquired in calibration clean room by means of an auxiliary optical system, have been processed in the photogrammetric pipeline using image correlation for the 3D model generation. The stereo reconstruction validation has been performed by comparing the STC DTMs (Digital Terrain Models) to an high resolution laser scanning 3D model of the stone samples as reference data. The latter has a much higher precision (ca. 20 μm) of the expected in-lab STC DTM (190 μm). Processing parameters have been varied in order to test their influence on the DTM generation accuracy. The main aim is to define the best illumination conditions and the process settings in order to obtain the best DTMs in terms of accuracy and completeness, seeking the best match between the mission constraints and the specific matching aspects that could affect the mapping process.
High resolution DTMs, suitable for geomorphological studies of planets and asteroids, are today among the main
scientific goals of space missions. In the framework of the BepiColombo mission, we are experimenting the use of
different matching algorithms as well as the use of different geometric transformation models between stereo pairs,
assessing their performances in terms of accuracy and computational efforts. Results obtained with our matching
software are compared with those of established software. The comparison of the performance of image matching being
the main objective of this work, all other steps of the DTM generation procedure have been made independent of the
matching software by using a common framework. Tests with different transformation models have been performed
using computer generated images as well as real HiRISE and LROC NAC images. The matching accuracy for real
images has been checked in terms of reconstruction error against DTMs of Mars and the Moon published online and
produced by the University of Arizona.
The Stereo Camera (STC) of the SIMBIO-SYS imaging suite of the BepiColombo ESA mission to Mercury is based on
an innovative and compact design in which the light independently collected by two optical channels at ±20° separation
with respect to nadir falls on a common bidimensional detector. STC adopts a novel stereo acquisition mode, based on
the push-frame concept, never used before on a space mission. To characterize this camera for obtaining the most
accurate data of the Mercury surface, standard calibration measurements have been performed. In addition, we also
wanted to demonstrate and characterize the capability of the instrument to reconstruct a 3D surface with the desired
accuracy by means of the stereo push-frame concept. To this end, a lab setup has been realized with an evaluation model
of STC, in which the problem of working at an essentially infinite object distance over hundred km baselines has been
overcome by means of a simple collimator and two precision rotators. The intrinsic and extrinsic parameters of the
camera have been obtained with standard stereo procedures, adapted to the specific case. The stereo validation has been
performed by comparing the shape of the target object accurately measured by laser scanning, with the shape
reconstructed by applying the adopted stereo algorithm to the acquired image pairs. The obtained results show the
goodness of this innovative validation technique, that will be applied also for validating the stereo capabilities of STC
flight model.
Automatic image orientation of close-range image blocks is becoming a task of increasing importance in the practice of
photogrammetry. Although image orientation procedures based on interactive tie point measurements do not require any
preferential block structure, the use of structured sequences can help to accomplish this task in an automated way.
Automatic orientation of image sequences has been widely investigated in the Computer Vision community. Here the
method is generally named "Structure from Motion" (SfM), or "Structure and Motion". These refer to the simultaneous
estimation of the image orientation parameters and 3D object points of a scene from a set of image correspondences.
Such approaches, that generally disregard camera calibration data, do not ensure an accurate 3D reconstruction, which is
a requirement for photogrammetric projects. The major contribution of SfM is therefore viewed in the photogrammetric
community as a powerful tool to automatically provide a dense set of tie points as well as initial parameters for a final
rigorous bundle adjustment. The paper, after a brief overview of automatic procedures for close-range image sequence
orientation, will show some characteristic examples. Although powerful and reliable image orientation solutions are
nowadays available at research level, there are certain questions that are still open. Thus the paper will also report some
open issues, like the geometric characteristics of the sequences, scene's texture and shape, ground constraints (control
points and/or free-network adjustment), feature matching techniques, outlier rejection and bundle adjustment models.
A photogrammetric strategy for the orientation of image sequences acquired by Mobile Mapping Vehicles (MMV) is presented. The motivations for this are twofold: to allow image georeferencing in short GPS outages for the MMV under development at the University of Parma, currently lacking an IMU; to improve the consistency of image georeferencing between asynchronous frames. The method may also contribute to limit the drift errors of low-cost integrated IMU/GPS systems in GPS outages. Drawing on techniques developed for structure and motion (S&M) reconstruction from image sequences and accounting for the specific conditions of the MMV imaging geometry, highly reliable multi-image matches are found, refining image orientation with a final bundle adjustment. Dealing with scenes with poor image texture and the automation of the convergence of the bundle to the solution are still problems. After successfully orienting image sequences up to about 200 m long, the accuracy of the orientation and reconstruction process was checked in a test field. Although not all constraints between synchronous image pairs are yet enforced, the accuracy degradation along the sequence was found to be still well within the specifications for the MMV. Furthermore curved path and possible solution to the poorness of tracked points are investigated.
The stability of a rock slope depends on the rock mass geo-structure and its discontinuities. Discontinuities show up at the rock surface as smooth and often plane surfaces. From their location and orientation the main families of fractures can be inferred and a stability analysis performed. To gather information on their distribution, surveys are typically carried out with geological compass and tape along scan lines, with obvious limitations and drawbacks. Here an highly automated image-based approach is presented to compute the required rock parameters: an accurate high resolution Digital Surface Model of the area of interest is generated from an image sequence and segmented in plane surfaces within a multi resolution RANSAC search, which returns location and orientation of each plane. To avoid measuring ground control points, the camera may be interfaced to a GPS receiver. Multiple overlapping and convergent images are captured to achieve good accuracy over the whole network, minimize occlusions and avoid poor object-camera relative geometry. The method is applied to the rock face of Corma di Machaby (Italy): the results are compared to those of a traditional survey with compass and to those of a laser scanner survey.
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