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A New Enhancement Filtering Approach for the Automatic Vector Conversion of the UAV Photogrammetry Output

  • Maria AlicandroEmail author
  • Donatella Dominici
  • Paolo Massimo Buscema
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11196)

Abstract

In the last decades the photogrammetry has undergone interesting innovation, both in terms of data processing and acquisition mode, to allow obtaining detailed 3D models useful for complete survey and important support for the management and recovery of cultural heritage and buildings. However, despite recent developments, the main photogrammetry outputs are raster data (ortophoto and DEM) and point clouds characterized by high informative content, but they are not typically extracted automatically. Automated feature detection is yet manual, time-consuming procedure and an active area of research. The raster to vector conversion is not direct, but transformations must be performed on the input data to convert the pixel values into features. Always, segmentations are preceded by filter technique to remove noise and to improve the conversion phase. However, remote sensing data and especially UAV photogrammetry output are the most complex to treat because of their heterogeneity (presence of different objects and shapes), the nature of sensor used and the different scale. In this work we experiment new enhancement filter to improve the automatic extraction of vector information for a UAV photogrammetry results of the facing walls of eminent church, symbol of the city of L’Aquila, the” Basilica of Santa Maria di Collemaggio”.

Keywords

Photogrammetry UAV Segmentation Filter enhancement 

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.University of L’AquilaL’AquilaItaly
  2. 2.Semeion Research Center of Sciences of CommunicationRomeItaly
  3. 3.Department of Mathematical and Statistical SciencesUniversity of ColoradoDenverUSA

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