Alessia Scardi
Compression and cloud screening for satellite images.
Rel. Enrico Magli. Politecnico di Torino, Corso di laurea magistrale in Ict For Smart Societies (Ict Per La Società Del Futuro), 2025
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Abstract
The increasing volume of Earth Observation (EO) data generated by the high-resolution satellites' sensors poses critical challenges to onboard storage, transmission, and real-time processing. The images collected during the space missions need to clearly show the surface of the Earth in order to be used in multiple contexts and fields: land cover classification, vegetation, ice and water analysis, atmospheric correction and mineral mapping. Unfortunately, the sky is not always clear of clouds, which degrade the information quality when appearing in the satellite images, often making major portions of the data unfit for further analysis and losing the very purpose the images were meant to serve.
Accurate cloud detection algorithms are required to discriminate cloudy pixels from cloud-free ones directly onboard the satellite to generate binary segmentation masks, exploited during the onboard compression stage
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