A New Two-Step Robust Surface Matching Approach for Three-Dimensional Georeferencing of Historical Digital Elevation Models

Aguilar, Fernando J.; Aguilar, Manuel A.; Fernández, Isabel; Negreiros, João; Delgado, Jorge; Pérez, José Luís

doi:10.1109/lgrs.2011.2175899

Cited by 12 publications

(8 citation statements)

References 10 publications

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“…However, the identification and quality of ground control in archival photography is often problematic. As a result, much research has been carried out in order to reduce the need for these costly and difficult to measure GCPs by means of surface matching (see, for example, Li et al, 2001;Mills et al, 2003Mills et al, , 2005Miller et al, 2008;Akca, 2010;Aguilar et al, 2012), or extracting GCPs from lidar-derived digital elevation models (DEMs) (James et al, 2006). Nowadays the results regarding the application of self-calibration to archival photography are extremely variable.…”

Section: Introductionmentioning

confidence: 99%

Accuracy Assessment of Commercial Self‐Calibrating Bundle Adjustment Routines Applied to Archival Aerial Photography

Aguilar

Fernández

et al. 2012

The Photogrammetric Record

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The use of archival or historical photography for photogrammetric purposes often involves a lack of data concerning the aerial cameras employed, difficulties in identifying control points on the photos and inappropriate conservation of the photography. When camera calibration parameters are unknown, they should be estimated by means of a self‐calibrating bundle adjustment. Several calibration models available in the Leica Photogrammetry Suite software have been tested on two archival datasets, captured in 1956 and 1977, covering the same working area. The accuracy of the dataset triangulation was found to depend significantly on the self‐calibration method and the number of ground control points used; when the latter ranged from six to nine per stereopair, self‐calibrating bundle adjustment techniques were found to slightly, but not always significantly, improve the photogrammetric capability of archival aerial photography. Thus, the adoption of self‐calibration cannot guarantee the improvement of results when working on poorly conserved imagery. Results from such datasets are very dependent on numerous local variables which cannot be extrapolated to other areas for the same camera since each dataset is unique and may present systematic errors of a different nature.

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Section: Introductionmentioning

confidence: 99%

Accuracy Assessment of Commercial Self‐Calibrating Bundle Adjustment Routines Applied to Archival Aerial Photography

Aguilar

Fernández

et al. 2012

The Photogrammetric Record

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“…Dataset AA‐02100301 also has both forward and side overlap, while 23S‐RAF‐0193 lacks side overlap. It is also likely that extreme elevation values in the photogrammetrically scanned datasets could be further reduced by smoothing and denoising processes, and coregistration techniques could be used in a subsequent step in order to improve their position relative to the ALS surface (Aguilar et al , ; Sevara, ; Risbøl et al , ). The extreme variation in the NPG dataset would make it difficult for these types of processes to be uniformly effective over the entirety of the surface, but some improvement might be gained.…”

Section: Discussionmentioning

confidence: 99%

Capturing the Past for the Future: an Evaluation of the Effect of Geometric Scan Deformities on the Performance of Aerial Archival Media in Image‐based Modelling Environments

Sevara

2016

Archaeological Prospection

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Image-based modelling (IBM) applications can be used to successfully extract two-and three-dimensional information from historic aerial and satellite imagery for use in archaeological and other landscape-oriented research. The robust and highly automated nature of these applications can allow for image matching and dense scene reconstruction, even when input images lack information necessary for processing in traditional photogrammetric workflows. However, the overall quality of the content derived from IBM applications can be directly influenced by a number of variables, including the manner in which archival content is digitized. Significant geometric distortion can be induced in the scanning process when using non-photogrammetric scanning devices, which can have a negative effect on the subsequent processing of scanned imagery and accuracy of derived content such as orthomosaics and digital elevation models (DEMs). While this is a well-known issue for users of high end photogrammetry packages, the advent of IBM applications has brought the use of photogrammetric-style techniques to a wider audience who may not be aware of the impact that geometric errors of this nature can have on the quality of derived data products. This issue is demonstrated here using a set of degraded historic World War II (WWII) Allied reconnaissance photographs that have been digitized on both photogrammetric and nonphotogrammetric platforms and subsequently processed in a well-known IBM application using identical processing parameters. The results are compared to those from a recently collected set of vertical stereopairs and an airborne laser scan derived DEM.

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“…This suggests that although the refinement process improves the overall quality of the hDEM, more work is needed to refine processing parameters in order to improve the result. A more robust coregistration process such as the approach developed by Aguilar et al (2012) which improves overall accuracy of hDEM alignment while better retaining historic landscape feature geometry could be implemented to further improve hDEM coregistration. This solution could also obviate the need for precision GCP collection and placement in circumstances where collecting such data could be difficult (Aguilar et al 2012:589).…”

Section: Elevation Model Refinementmentioning

confidence: 99%

Top Secret Topographies: Recovering Two and Three-Dimensional Archaeological Information from Historic Reconnaissance Datasets Using Image-Based Modelling Techniques

Sevara

2013

International Journal of Heritage in the Digital Era

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Historic aerial reconnaissance photographs are a valuable resource for archaeological and other landscape-oriented research. However, they are often difficult to access and convert into useable geospatial datasets. This article outlines a workflow for producing georeferenced two and three-dimensional data products from a range of historic frame camera imagery for use in GIS environments using readily available cost-effective computer vision based techniques. These techniques are highly automated and thus more accessible to non-specialist users, and are often able to recover meaningful, useable data from imagesets which can be difficult to process using traditional photogrammetric techniques. This approach is demonstrated on a number of historical datasets which cover the Kreuttal region of Lower Austria, an archaeologically rich area which contains traces of human occupation and land-use from the Neolithic to the Modern Historic periods. WWII Allied reconnaissance aerial photographs and declassified imagery intelligence data from the US Government HEXAGON program are processed using these techniques and the resulting orthophotograph mosaics and historic digital elevation models are analysed against high-accuracy reference datasets of known quality. In addition to obviating some of the difficulties inherent in processing historic imagery, this approach also demonstrates that historic remote sensing images can be put to novel uses that far exceed their intended purposes.

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A New Two-Step Robust Surface Matching Approach for Three-Dimensional Georeferencing of Historical Digital Elevation Models

Cited by 12 publications

References 10 publications

Accuracy Assessment of Commercial Self‐Calibrating Bundle Adjustment Routines Applied to Archival Aerial Photography

Accuracy Assessment of Commercial Self‐Calibrating Bundle Adjustment Routines Applied to Archival Aerial Photography

Capturing the Past for the Future: an Evaluation of the Effect of Geometric Scan Deformities on the Performance of Aerial Archival Media in Image‐based Modelling Environments

Top Secret Topographies: Recovering Two and Three-Dimensional Archaeological Information from Historic Reconnaissance Datasets Using Image-Based Modelling Techniques

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