Visibility Detector for Time Series of Spectrally Limited Satellite Imagers
Tristan Dagobert, Jean-Michel Morel, Carlo de Franchis
⚠ This is a preprint. It may change before it is accepted for publication.

Abstract

This article addresses the problem of estimating scene visibility in time series of satellite images. We are especially focused on satellites with few spectral bands but with high revisit frequency. Our approach exploits the redundancy of information acquired during these revisits. It is based on an unsupervised algorithm that tracks local ground textures across time and detects ruptures caused by opaque clouds, haze, cirrus and shadows. Experiments have been carried out on 18 Planet times series representing various locations. These time series come with hand-made labeled ground truth that we make available to the scientific community. We compare the results obtained with those of the PlanetScope algorithm and demonstrate the effectiveness of the proposed method: success rates of 94% and 84% are reached for the visible and occulted regions classification.

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