TEMPORAL REPETITION DETECTION FOR GROUND VISIBILITY ASSESSMENT

Autor: R. Grompone von Gioi, C. Hessel, T. Dagobert, J. M. Morel, C. de Franchis
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-2-2020, Pp 829-835 (2020)
Druh dokumentu: article
ISSN: 2194-9042
2194-9050
DOI: 10.5194/isprs-annals-V-2-2020-829-2020
Popis: 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.
Databáze: Directory of Open Access Journals