Scipediacontent: Scipediacontent moved page Draft Content 541473803 to Uzkent et al 2019a

2021-02-01T18:26:36Z

Scipediacontent moved page Draft Content 541473803 to Uzkent et al 2019a

Scipediacontent: Created page with " == Abstract == Satellite images hold great promise for continuous environmental monitoring and earth observation. Occlusions cast by clouds, however, can severely limit cove..."

2021-02-01T18:26:31Z

Created page with " == Abstract == Satellite images hold great promise for continuous environmental monitoring and earth observation. Occlusions cast by clouds, however, can severely limit cove..."

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== Abstract ==

Satellite images hold great promise for continuous environmental monitoring and earth observation. Occlusions cast by clouds, however, can severely limit coverage, making ground information extraction more difficult. Existing pipelines typically perform cloud removal with simple temporal composites and hand-crafted filters. In contrast, we cast the problem of cloud removal as a conditional image synthesis challenge, and we propose a trainable spatiotemporal generator network (STGAN) to remove clouds. We train our model on a new large-scale spatiotemporal dataset that we construct, containing 97640 image pairs covering all continents. We demonstrate experimentally that the proposed STGAN model outperforms standard models and can generate realistic cloud-free images with high PSNR and SSIM values across a variety of atmospheric conditions, leading to improved performance in downstream tasks such as land cover classification.

Comment: Accepted to WACV 2020

== Original document ==

The different versions of the original document can be found in:

* [http://arxiv.org/abs/1912.06838 http://arxiv.org/abs/1912.06838]

* [http://arxiv.org/pdf/1912.06838 http://arxiv.org/pdf/1912.06838]

* [http://xplorestaging.ieee.org/ielx7/9087828/9093261/09093564.pdf?arnumber=9093564 http://xplorestaging.ieee.org/ielx7/9087828/9093261/09093564.pdf?arnumber=9093564],
: [http://dx.doi.org/10.1109/wacv45572.2020.9093564 http://dx.doi.org/10.1109/wacv45572.2020.9093564]

* [https://dblp.uni-trier.de/db/journals/corr/corr1912.html#abs-1912-06838 https://dblp.uni-trier.de/db/journals/corr/corr1912.html#abs-1912-06838],
: [https://academic.microsoft.com/#/detail/3025649582 https://academic.microsoft.com/#/detail/3025649582]

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Uzkent et al 2019a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 541473803 to Uzkent et al 2019a

Scipediacontent: Created page with " == Abstract == Satellite images hold great promise for continuous environmental monitoring and earth observation. Occlusions cast by clouds, however, can severely limit cove..."