TY - GEN
T1 - Detecting Forged Sentinel-2 Images Through Parallax-Based Cloud Analysis
AU - Serfaty, Matthieu
AU - Bammey, Quentin
AU - Nikoukhah, Tina
AU - von Gioi, Rafael Grompone
AU - de Franchis, Carlo
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - The availability and significance of satellite imagery in our world is continuously growing. Satellite images now play a crucial role in various applications such as weather forecasting, greenhouse gas monitoring, agricultural crop health assessment, and external security. However, this also exposes them to malicious attacks aimed at hiding or manipulating information. Forensic analysis is, therefore, a necessary shield against disinformation and disruption attempts in these areas. While forensic analysis of photographs has received considerable academic attention in recent years, the same cannot be said for satellite imagery. In this study, we present two methodologies to create realistic datasets of images forged with added clouds, that may inconspicuously hide information. We show results produced by state-of-the-art forensic methods are unable to detect the forged satellite images. To overcome this problem, we propose a parallax-based method to detect inconsistent satellite images.
AB - The availability and significance of satellite imagery in our world is continuously growing. Satellite images now play a crucial role in various applications such as weather forecasting, greenhouse gas monitoring, agricultural crop health assessment, and external security. However, this also exposes them to malicious attacks aimed at hiding or manipulating information. Forensic analysis is, therefore, a necessary shield against disinformation and disruption attempts in these areas. While forensic analysis of photographs has received considerable academic attention in recent years, the same cannot be said for satellite imagery. In this study, we present two methodologies to create realistic datasets of images forged with added clouds, that may inconspicuously hide information. We show results produced by state-of-the-art forensic methods are unable to detect the forged satellite images. To overcome this problem, we propose a parallax-based method to detect inconsistent satellite images.
UR - https://www.scopus.com/pages/publications/105007133596
U2 - 10.1007/978-3-031-91838-4_8
DO - 10.1007/978-3-031-91838-4_8
M3 - Conference contribution
AN - SCOPUS:105007133596
SN - 9783031918377
T3 - Lecture Notes in Computer Science
SP - 125
EP - 141
BT - Computer Vision – ECCV 2024 Workshops, Proceedings
A2 - Del Bue, Alessio
A2 - Canton, Cristian
A2 - Pont-Tuset, Jordi
A2 - Tommasi, Tatiana
PB - Springer Science and Business Media Deutschland GmbH
T2 - Workshops that were held in conjunction with the 18th European Conference on Computer Vision, ECCV 2024
Y2 - 29 September 2024 through 4 October 2024
ER -