A CNN Cloud Detector for Panchromatic Satellite Images

M. Rodríguez; J. Anger; C. de Franchis; C. Hessel; G. Facciolo; R. Grompone; J.-M. Morel

doi:10.1109/IGARSS47720.2021.9554059

A CNN Cloud Detector for Panchromatic Satellite Images

M. Rodríguez
, J. Anger
, C. de Franchis
, C. Hessel
, G. Facciolo
, R. Grompone
, J.-M. Morel

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

Abstract

Cloud detection is a crucial step for automatic satellite image analysis. Some cloud detection methods exploit specially designed spectral bands, other base the detection on time series, or on the inter-band delay in push-broom satellites. Nevertheless many use cases occur where these methods do not apply. This paper describes a convolutional neural network for cloud detection in panchromatic and single-frame images. Only a per-image annotation is required, indicating which images contain clouds and which are cloud-free. Our experiments show that, in spite of using less information, the proposed method produces competitive results. © 2021 IEEE

Original language	English
Title of host publication	IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium
Subtitle of host publication	PROCEEDINGS
Publisher	IEEE
Pages	4964-4967
ISBN (Electronic)	978-1-6654-0369-6, 978-1-6654-0368-9
ISBN (Print)	978-1-6654-4762-1
DOIs	https://doi.org/10.1109/IGARSS47720.2021.9554059
Publication status	Published - 2021
Externally published	Yes
Event	2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2021) - Virtual, Brussels, Belgium Duration: 11 Jul 2021 → 16 Jul 2021

Publication series

Name
ISSN (Print)	2153-6996
ISSN (Electronic)	2153-7003

Conference

Conference	2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2021)
Place	Belgium
City	Brussels
Period	11/07/21 → 16/07/21

Funding

Work partly financed by IDEX Paris-Saclay IDI 2016, ANR-11-IDEX0003-02, Office of Naval research grant N00014-17-1-2552, DGA Astrid project < filmer la Terre> n oANR-17-ASTR-0013-01, MENRT. The Titan V used for this research was donated by the NVIDIA Corporation.

Research Keywords

Cloud detector
CNN
panchromatic
satellite images
single-band

Access Output

10.1109/IGARSS47720.2021.9554059

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

@inproceedings{affe2006bb8045c3a595ad2c74430036,

title = "A CNN Cloud Detector for Panchromatic Satellite Images",

abstract = "Cloud detection is a crucial step for automatic satellite image analysis. Some cloud detection methods exploit specially designed spectral bands, other base the detection on time series, or on the inter-band delay in push-broom satellites. Nevertheless many use cases occur where these methods do not apply. This paper describes a convolutional neural network for cloud detection in panchromatic and single-frame images. Only a per-image annotation is required, indicating which images contain clouds and which are cloud-free. Our experiments show that, in spite of using less information, the proposed method produces competitive results. {\textcopyright} 2021 IEEE",

keywords = "Cloud detector, CNN, panchromatic, satellite images, single-band",

author = "M. Rodr{\'i}guez and J. Anger and \{de Franchis\}, C. and C. Hessel and G. Facciolo and R. Grompone and J.-M. Morel",

year = "2021",

doi = "10.1109/IGARSS47720.2021.9554059",

language = "English",

isbn = "978-1-6654-4762-1",

publisher = "IEEE",

pages = "4964--4967",

booktitle = "IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium",

address = "United States",

note = "2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2021) ; Conference date: 11-07-2021 Through 16-07-2021",

}

Rodríguez, M, Anger, J, de Franchis, C, Hessel, C, Facciolo, G, Grompone, R & Morel, J-M 2021, A CNN Cloud Detector for Panchromatic Satellite Images. in IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium: PROCEEDINGS. IEEE, pp. 4964-4967, 2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2021), Brussels, Belgium, 11/07/21. https://doi.org/10.1109/IGARSS47720.2021.9554059

A CNN Cloud Detector for Panchromatic Satellite Images. / Rodríguez, M.; Anger, J.; de Franchis, C. et al.
IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium: PROCEEDINGS. IEEE, 2021. p. 4964-4967.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - A CNN Cloud Detector for Panchromatic Satellite Images

AU - Rodríguez, M.

AU - Anger, J.

AU - de Franchis, C.

AU - Hessel, C.

AU - Facciolo, G.

AU - Grompone, R.

AU - Morel, J.-M.

PY - 2021

Y1 - 2021

N2 - Cloud detection is a crucial step for automatic satellite image analysis. Some cloud detection methods exploit specially designed spectral bands, other base the detection on time series, or on the inter-band delay in push-broom satellites. Nevertheless many use cases occur where these methods do not apply. This paper describes a convolutional neural network for cloud detection in panchromatic and single-frame images. Only a per-image annotation is required, indicating which images contain clouds and which are cloud-free. Our experiments show that, in spite of using less information, the proposed method produces competitive results. © 2021 IEEE

AB - Cloud detection is a crucial step for automatic satellite image analysis. Some cloud detection methods exploit specially designed spectral bands, other base the detection on time series, or on the inter-band delay in push-broom satellites. Nevertheless many use cases occur where these methods do not apply. This paper describes a convolutional neural network for cloud detection in panchromatic and single-frame images. Only a per-image annotation is required, indicating which images contain clouds and which are cloud-free. Our experiments show that, in spite of using less information, the proposed method produces competitive results. © 2021 IEEE

KW - Cloud detector

KW - CNN

KW - panchromatic

KW - satellite images

KW - single-band

UR - https://www.scopus.com/pages/publications/85129838343

UR - https://www.scopus.com/pages/publications/85129838343#tab=impact

U2 - 10.1109/IGARSS47720.2021.9554059

DO - 10.1109/IGARSS47720.2021.9554059

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 978-1-6654-4762-1

SP - 4964

EP - 4967

BT - IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium

PB - IEEE

T2 - 2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2021)

Y2 - 11 July 2021 through 16 July 2021

ER -

A CNN Cloud Detector for Panchromatic Satellite Images

Abstract

Publication series

Conference

Funding

Research Keywords

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this