ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-2-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 829–835, 2020
https://doi.org/10.5194/isprs-annals-V-2-2020-829-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 829–835, 2020
https://doi.org/10.5194/isprs-annals-V-2-2020-829-2020

  03 Aug 2020

03 Aug 2020

TEMPORAL REPETITION DETECTION FOR GROUND VISIBILITY ASSESSMENT

R. Grompone von Gioi1, C. Hessel1, T. Dagobert1, J. M. Morel1, and C. de Franchis1,2 R. Grompone von Gioi et al.
  • 1Université Paris-Saclay, CNRS, ENS Paris-Saclay, Centre Borelli, 94235, Cachan, France
  • 2Kayrros SAS

Keywords: ground visibility detection, cloud detection, satellite time series, a contrario framework

Abstract. Assessing ground visibility is a crucial step in automatic satellite image analysis. Nevertheless, several recent Earth observation satellite constellations lack specially designed spectral bands and use a frame camera, precluding spectrum-based and parallax-based cloud detection methods. An alternative approach is to detect the parts of each image where the ground is visible. This can be done by comparing locally pairs of registered images in a temporal series: matching regions are necessarily cloud free. Indeed, the ground has persistent patterns that can be observed repetitively in the time series while the appearance of clouds changes at each date. To detect reliably the “visible” ground, we propose here an a contrario local image matching method coupled with an efficient greedy algorithm.