Cloud masking is of central importance to the Earth Observation community. This paper
deals with the problem of detecting clouds in visible and multispectral imagery from high …

Cloud Detection is an important pre-processing step for any application involving remote
sensing data. This paper presents a deep learning based CloudX-Net architecture, that can …

Cloud detection is an important preprocessing step for the precise application of optical
satellite imagery. In this paper, we propose a deep learning based cloud detection method …

The systematic monitoring of the Earth using optical satellites is limited by the presence of
clouds. Accurately detecting these clouds is necessary to exploit satellite image archives in …

A stable and reliable cloud detection algorithm is an important step of optical satellite data
preprocessing. Existing threshold methods are mostly based on classifying spectral features …

Cloud detection algorithms are crucial in many remote-sensing applications to allow an
optimized processing of the acquired data, without the interference of the cloud fields above …

Reliable detection of clouds is a critical pre-processing step in optical satellite based remote
sensing. Currently, most methods are based on classifying invidual pixels from their spectral …

Cloud detection in satellite images is an important first-step in many remote sensing
applications. This problem is more challenging when only a limited number of spectral …

Cloud detection is the task of detecting cloud areas in remote sensing images (RSIs), and it
has attracted extensive research interest. Recently, deep learning (DL)-based methods have …

Cloud detection is an important and difficult task in the pre-processing of satellite remote
sensing data. The results of traditional cloud detection methods are often unsatisfactory in …