The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B1-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 389–398, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-389-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 389–398, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-389-2022
 
30 May 2022
30 May 2022

ENHANCING CONTRAST OF IMAGES TO IMPROVE GEOMETRIC ACCURACY OF A UAV PHOTOGRAMMETRY PROJECT

S. Motayyeb1, S. A. Fakhri2, M. Varshosaz3, and S. Pirasteh4 S. Motayyeb et al.
  • 1Dept. of Photogrammetry and Remote Sensing, School of Surveying and Geospatial Engineering, University College of Engineering, University of Tehran, Tehran, Iran
  • 2Dept. of Geomatic Engineering, Faculty of Civil Engineering and Transportation, University of Isfahan, Isfahan, Iran
  • 3Dept. of Engineering, K. N. Toosi University of Technology, Tehran, Iran
  • 4Dept. of Surveying and Geoinformatics, Faculty of Geosciences and Environmental Engineering (FGEE), Southwest Jiaotong University, Chengdu 611756, S.P., China

Keywords: UAV photogrammetry, image contrast enhancement, image matching, point cloud

Abstract. In recent years, Unmanned Aerial Vehicles (UAVs) have become popular tools in mapping applications. In such applications, the image motion, bad lighting effects, and poor texture all directly affect the quality of the derived tie points, which in turn imposes constraints on image extraction and may lead to a low accuracy point cloud. This paper proposes a contrast enhancement technique to improve the accuracy of a photogrammetric model created using UAV images. The luminance component (Y) in the YIQ color space is normalized using the sigmoid function, and the low contrast images are enhanced using the Contrast-Limited Adaptive Histogram Equalization (CLAHE) on the luminosity component. To evaluate the proposed method, three-dimensional models were created using images acquired by the Phantom 4 Pro UAV in three distinct places and at altitudes of 20, 40, 60, 80, and 90 meters. The results showed that enhancing the contrast of images increased the number of tie points and reduced reprojection error by approximately 10%. It also improved the resolution of the digital elevation model by approximately 2cm/pixel while greatly improving the texture and quality with respect to that developed using the original images.