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Title
Close-range imaging, long-range vision



IMAGE COMBINATION INTO LARGE VIRTUAL IMAGES FOR FAST 3D MODELLING OF ARCHAEOLOGICAL
SITES
Maria Pateraki", Emmanuel Baltsavias", Petros Patias"
"Institute of Geodesy and Photogrammetry, ETH-Hoenggerberg, CH-8093, Zurich, Switzerland
(maria, manos)@geod.baug.ethz.ch
"Department of Cadastre Photogrammetry and Cartography, Aristotle University of Thessaloniki, Univ.Box 473, GR 54006,
Thessaloniki, Greece
patias@topo.auth.gr
WG V/4
KEY WORDS: documentation, archaeology, combination, matching, DSM, pre-processing.
ABSTRACT:
In archaeological sites there are often several levels of ruins when the site has been constructed upon other ancient or prehistorical
sites. It is very important for the archaeological research to map and monitor each step of the excavation. The traditional way for
mapping of excavation is time consuming. Digital photogrammetry enables instead fast acquisition and processing of the data. Con-
tinuous excavation reveals different levels of findings coming from different chronological periods, images have to be acquired be-
fore findings from each level are removed and excavation continues. Therefore, the storage of data and processing time increases due
to the number of images acquired from the excavation site. Apart from that, the images are acquired from amateurs, with less experi-
ence in acquisition techniques. A method has therefore been developed to transform many individual images into larger virtual im-
ages which can be considered of being of a normal central projection. Images can be combined under the assumption that the accu-
racy is sufficient for archaeological documentation. For the generation of each undistorted virtual image the Brown distortion model
has been used. The model gives the corrections from the distorted to the undistorted image, therefore the invert transformation has to
be calculated through an iterative approach, using the non-linear set of Brown equations. For the generation of the virtual images 2
strips were used, each consisting of 3-4 images with 70-8096 overlap. The strips form two virtual images with sufficient overlap to
extract a DSM. The images had to be enhanced and be radiometrically balanced. In this way more features can be extracted and
mapped, even small structures that are covered with dust or lie in shadowed or overexposed areas. Methods are presented to reduce
noise, enhance edges and contrast. They are essential for higher image quality and further processing. Results from automatic DSM
generation using virtual images are presented, using a new multi-pass adaptive matching algorithm. The algorithm uses features as
primitives. Through a multi-pass technique at each extracted feature and computed quality measures, a more robust quality control
ensures higher reliability of the final result. A comparison of automatic DSM generation from the separate models of raw images and
the two virtual images is done. All results are compared with a manual extracted DSM and presented.
Koistinen (2000) use concentric image sequences, which can be
projected onto the cylinder surface and adjacent frames com-
1. INTRODUCTION bined to a panoramic image.
The excavation site is the ancient city of Eleftherna in Crete
(Fig. 1, 2), Greece. Among few excavation holes at the archeo-
logical site a specific one has been selected for processing (4m
x 4m). The images have been acquired from amateurs with less
experience in the acquisition techniques and therefore the geo-
metrical configuration of the block of images and the camera
positions and rotations were not optimal for precise bundle ad-
justment and self calibration and consequently for extraction of
3D information.
In the last years, digital photogrammetry became a major tool in
archaeology. Photogrammetric techniques are used in order to
record and document the findings of an archaeological site area.
In some archaeological sites there are different levels of ruins,
coming from different chronological periods, since in most
cases the site has been constructed upon other older sites. The
different levels of ruins have to be recorded as the excavation
progresses and therefore a significant amount of data has to be
stored for further processing and mapping. In each excavation
site, there are several excavation holes and for each one of these
different levels of ruins may exist. Additionally the number of
images acquired depends on the size of the excavation hole, in-
creasing significantly the amount of acquired images. The
method presented in this paper aims at reduction of the data
storage and easier handling by combining the acquired images
into large virtual images under the assumption that the accuracy
is sufficient for archaeological documentation. Consequently,
the virtual image can substitute a strip of images and can be
used for further processing, as DSM generation and 3D map-
ping. Generation of virtual images through projective transfor-
mation is discussed in (Stephani, 1999), thus one image is trans-
formed and not sequence of images. Póntinen (2000) and Figure 1. Location of test site in Crete (highlighted)

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