ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3, 33-40, 2014
https://doi.org/10.5194/isprsannals-II-3-33-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
07 Aug 2014
Automatic Georeferencing of a Heritage of old analog aerial Photographs
I. Cléri1, M. Pierrot-Deseilligny2, and B. Vallet3 1Université Paris-Est, IGN, SRIG, MATIS, EDITE, 73 avenue de Paris, 94160 Saint Mandé, France
2IGN, Laboratoire LOEMI, Université Paris-Est, 73 avenue de Paris, 94165 Saint-Mandé cedex, France
3Université Paris-Est, IGN, SRIG, MATIS, 73 avenue de Paris, 94160 Saint Mandé, France
Keywords: Registration, Automation, Georeferencing, Matching, Analog, Aerial, Photography, Database Abstract. Historical photographs become widely used in geographical and environmental applications. Their enhancement involves converting them into georeferenced data, such as orthoimages or digital models. However no ground control points are available unlike in current image processing, and many problems such as image noise, landscape modifications, perspective distortion and unknown sensor calibration prevent automatic tie-point retrieval with current orthoimages. That is why photograph georeferencing remains a manual and time-consuming task. A novel method is presented in this paper to register photographs with current topographic database using line feature matching. Indeed, geometrical considerations only let avoid high radiometric difference issues when dealing with current orthoimages. Besides topographic database use lets selecting stable through time features, such as road network and historical buildings. A multi-scale approach allows very coarse georeferencing initialization, which can be set manually by a minimum number of ground control points per image set. At each scale an iterative processing improves the line matching and the registration model estimation at the same time. Finally, building integration makes registration more reliable for off-ground objects. Results are promising as georeferencing is much improved and its estimation converges in all test cases.
Conference paper (PDF, 7247 KB)


Citation: Cléri, I., Pierrot-Deseilligny, M., and Vallet, B.: Automatic Georeferencing of a Heritage of old analog aerial Photographs, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3, 33-40, https://doi.org/10.5194/isprsannals-II-3-33-2014, 2014.

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