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Cloud Image Prior: Single Image Cloud Removal
2021Cloud removal from satellite imagery is a well-known problem in both remote sensing and deep learning. Many methods have been developed to address the cloud removal problem in a supervised setting. These methods require gathering of huge datasets to learn the mapping from cloudy images to cloud-free images. In this paper, we address cloud removal as an
Anirudh Maiya, S. S. Shylaja
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Cloud and cloud shadow removal of landsat 8 images using Multitemporal Cloud Removal method
2017 6th International Conference on Agro-Geoinformatics, 2017Cloud and cloud shadow cover on satellite images limit remote sensing and geo-information systems (GIS) applications in all application areas, especially for change detection and time series analyses. A novel method of cloud and cloud shadow removal called Multitemporal Cloud Removal (MCR) is proposed in this paper.
Danang Surya Candra +2 more
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Cloud Shadow Removal Based on Cloud Transmittance Estimation
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018This paper proposes a method of cloud shadow removal for multispectral images to retrieve the ground reflectance of areas shadowed by clouds. Cloud shadows are cast when incident direct solar irradiance gets attenuated by clouds. To retrieve the ground reflectance of the shadowed pixels, it is required to estimate pixel-wise attenuation factor for the ...
Madhuri Nagare +4 more
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International Journal of Computer Applications in Technology, 2015
This paper describes a technique - efficient cloud detection and removal ECDR algorithm based on remote sensing information. It is obvious that cloud masking has been a challenging risk in receiving the information from the satellite sensor images. For instance, in-paint and multitemporal averaging method, which are existing approaches implemented ...
E. Menaka, S. Suresh Kumar, M. Bharathi
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This paper describes a technique - efficient cloud detection and removal ECDR algorithm based on remote sensing information. It is obvious that cloud masking has been a challenging risk in receiving the information from the satellite sensor images. For instance, in-paint and multitemporal averaging method, which are existing approaches implemented ...
E. Menaka, S. Suresh Kumar, M. Bharathi
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Autoencoding approach to the cloud removal problem
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017We propose in this work new strategies to reconstruct areas obscured by opaque clouds in multispectral images. They are based on an autoencoder (AE) neural network which opportunely models the relationships between a given source (cloud-free) image and a target (cloud-contaminated) image.
S. Malek, F. Melgani
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Closest Spectral Fit for Removing Clouds and Cloud Shadows
Photogrammetric Engineering & Remote Sensing, 2009Completely cloud-free remotely sensed images are preferred, but they are not always available. Although the average cloud coverage for the entire planet is about 40 percent, the removal of clouds and cloud shadows is rarely studied. To address this problem, a closest spectral fit method is developed to replace cloud and cloud-shadow pixels with their ...
Qingmin Meng +3 more
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Cloud effects removal via sparse representation
2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015Optical remote sensing images are often contaminated by the presence of clouds. The development of cloud effect removal techniques can maximize the usefulness of multispectral or hyperspectral images collected in the spectral range from visible to mid infrared.
Meng Xu, Xiuping Jia, Mark Pickering
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