ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume II-3
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3, 33–40, 2014
https://doi.org/10.5194/isprsannals-II-3-33-2014
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3, 33–40, 2014
https://doi.org/10.5194/isprsannals-II-3-33-2014

  07 Aug 2014

07 Aug 2014

Automatic Georeferencing of a Heritage of old analog aerial Photographs

I. Cléri1, M. Pierrot-Deseilligny2, and B. Vallet3 I. Cléri et al.
  • 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.