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Since airport images contain a large amount of coordinates, textures and other information, and as the accuracy of three-dimensional models continues to improve, the resolution of airport recognition images continues to increase, making image processing more complex. This article relates the position of the terrain origin (or shooting origin) in photogrammetry to the origin in the world coordinate system. According to the principle of photogrammetry, photos are taken at oblique angles from different distances and in different directions to form an oblique photography system. When taking photos, in addition to considering the spatial position relationship, it must also consider the azimuth angle, tilt angle, etc. to determine the shooting location and angle of view of the photo, as well as the time and lighting conditions during the shooting. In this paper, the recall rate of the method is 93.12%, and the residual spectrum algorithm is 71.24%. It is a very promising method to identify and classify aircraft ground objects using tilted photography data. Compared with the existing algorithm, the method given in this paper has greatly improved the accuracy and efficiency.

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The Application of High-Resolution Airport Oblique Photography Data in the Identification and Classification of Airport Surface Objects

  • 章节

  • 发表日期：

    2025年

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  • Lijun Yuan,
  • Yewen Wu,
  • Weixiang Ding,
  • Jun Le,
  • Ning Wu,
  • Guanghui Wang,
  • Chongxiao Wang

摘要

Since airport images contain a large amount of coordinates, textures and other information, and as the accuracy of three-dimensional models continues to improve, the resolution of airport recognition images continues to increase, making image processing more complex. This article relates the position of the terrain origin (or shooting origin) in photogrammetry to the origin in the world coordinate system. According to the principle of photogrammetry, photos are taken at oblique angles from different distances and in different directions to form an oblique photography system. When taking photos, in addition to considering the spatial position relationship, it must also consider the azimuth angle, tilt angle, etc. to determine the shooting location and angle of view of the photo, as well as the time and lighting conditions during the shooting. In this paper, the recall rate of the method is 93.12%, and the residual spectrum algorithm is 71.24%. It is a very promising method to identify and classify aircraft ground objects using tilted photography data. Compared with the existing algorithm, the method given in this paper has greatly improved the accuracy and efficiency.