ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume V-2-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 871–876, 2020
https://doi.org/10.5194/isprs-annals-V-2-2020-871-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 871–876, 2020
https://doi.org/10.5194/isprs-annals-V-2-2020-871-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  03 Aug 2020

03 Aug 2020

CORRECTION OF SYSTEMATIC RADIOMETRIC INHOMOGENEITY IN SCANNED AERIAL CAMPAIGNS USING PRINCIPAL COMPONENT ANALYSIS

L. Lelégard, A. Le Bris, and S. Giordano L. Lelégard et al.
  • LASTIG, Université Gustave Eiffel, ENSG, IGN, F-94160 Saint-Mandé, France

Keywords: Analogue Photography, Airborne Imagery, Radiometry, Orthophotomosaic, Hotspot Correction, PCA, KLT

Abstract. Orthophotomosaic is defined as a single image that can be layered on a map. The term “mosaic” implies that it is produced from a set of images, usually aerial images. Even if these images are taken during cloudless period, they are impaired by radiometric inhomogeneity mostly due to atmospheric phenomena, like hotspot, haze or high altitude clouds shadows as well as imaging device systematisms, like lens vignetting. These create some unsightly radiometric inhomogeneity in the orthophotomosaic that could be corrected by using a Wallis filter. Yet this solution leads to a significant loss of contrast at small scales. This work introduces an alternative to Wallis filter by considering some systematic radiometric behaviours in the images through a principal component analysis process.