Comprehensive structure voting docked ship detection from high-resolution optical satellite images based on combined multi-orientation sparse representation

Yin Zhuang; He Chen; Haotian Zhou; Liang Chen; Fukun Bi

doi:10.1109/IGARSS.2018.8519112

Comprehensive structure voting docked ship detection from high-resolution optical satellite images based on combined multi-orientation sparse representation

Yin Zhuang, He Chen^*, Haotian Zhou, Liang Chen, Fukun Bi

^*Corresponding author for this work

School of Information and Electronics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Inshore ship detection from high-resolution (HR) optical satellite images is a hot research field. However, HR ships multi-scale and multi-orientation characters and harbor scene various interferences affect docked ship detection performance. Therefore, we proposed a multi-orientations sparse dictionaries (MOSDs) algorithm combining with comprehensive structure voting (CSV) to address existed problem and achieve refined docked ship contour region proposal (RP). Moreover, the comparing experiments use a lot of Google Earth harbour images to demonstrate proposed method effectiveness and robustness of HR ships multi-scale and –orientation changing and various harbour background interferences of docked ship detection.

Original language	English
Title of host publication	2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	733-736
Number of pages	4
ISBN (Electronic)	9781538671504
DOIs	https://doi.org/10.1109/IGARSS.2018.8519112
Publication status	Published - 31 Oct 2018
Event	38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Valencia, Spain Duration: 22 Jul 2018 → 27 Jul 2018

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2018-July

Conference

Conference	38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Country/Territory	Spain
City	Valencia
Period	22/07/18 → 27/07/18

Keywords

Combined multi-orientation sparse dictionaries
Comprehensive structure voting
High-resolution
Inshore ship detection
Optical satellite image

Access to Document

10.1109/IGARSS.2018.8519112

Cite this

Zhuang, Y., Chen, H., Zhou, H., Chen, L., & Bi, F. (2018). Comprehensive structure voting docked ship detection from high-resolution optical satellite images based on combined multi-orientation sparse representation. In 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings (pp. 733-736). Article 8519112 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2018-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2018.8519112

Zhuang, Yin ; Chen, He ; Zhou, Haotian et al. / Comprehensive structure voting docked ship detection from high-resolution optical satellite images based on combined multi-orientation sparse representation. 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 733-736 (International Geoscience and Remote Sensing Symposium (IGARSS)).

@inproceedings{89ae66802abe4f108c7e7072902d1647,

title = "Comprehensive structure voting docked ship detection from high-resolution optical satellite images based on combined multi-orientation sparse representation",

abstract = "Inshore ship detection from high-resolution (HR) optical satellite images is a hot research field. However, HR ships multi-scale and multi-orientation characters and harbor scene various interferences affect docked ship detection performance. Therefore, we proposed a multi-orientations sparse dictionaries (MOSDs) algorithm combining with comprehensive structure voting (CSV) to address existed problem and achieve refined docked ship contour region proposal (RP). Moreover, the comparing experiments use a lot of Google Earth harbour images to demonstrate proposed method effectiveness and robustness of HR ships multi-scale and –orientation changing and various harbour background interferences of docked ship detection.",

keywords = "Combined multi-orientation sparse dictionaries, Comprehensive structure voting, High-resolution, Inshore ship detection, Optical satellite image",

author = "Yin Zhuang and He Chen and Haotian Zhou and Liang Chen and Fukun Bi",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 ; Conference date: 22-07-2018 Through 27-07-2018",

year = "2018",

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doi = "10.1109/IGARSS.2018.8519112",

language = "English",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

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Zhuang, Y , Chen, H, Zhou, H, Chen, L & Bi, F 2018, Comprehensive structure voting docked ship detection from high-resolution optical satellite images based on combined multi-orientation sparse representation. in 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings., 8519112, International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2018-July, Institute of Electrical and Electronics Engineers Inc., pp. 733-736, 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, 22/07/18. https://doi.org/10.1109/IGARSS.2018.8519112

Comprehensive structure voting docked ship detection from high-resolution optical satellite images based on combined multi-orientation sparse representation. / Zhuang, Yin ; Chen, He; Zhou, Haotian et al.
2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 733-736 8519112 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Comprehensive structure voting docked ship detection from high-resolution optical satellite images based on combined multi-orientation sparse representation

AU - Zhuang, Yin

AU - Chen, He

AU - Zhou, Haotian

AU - Chen, Liang

AU - Bi, Fukun

PY - 2018/10/31

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AB - Inshore ship detection from high-resolution (HR) optical satellite images is a hot research field. However, HR ships multi-scale and multi-orientation characters and harbor scene various interferences affect docked ship detection performance. Therefore, we proposed a multi-orientations sparse dictionaries (MOSDs) algorithm combining with comprehensive structure voting (CSV) to address existed problem and achieve refined docked ship contour region proposal (RP). Moreover, the comparing experiments use a lot of Google Earth harbour images to demonstrate proposed method effectiveness and robustness of HR ships multi-scale and –orientation changing and various harbour background interferences of docked ship detection.

KW - Combined multi-orientation sparse dictionaries

KW - Comprehensive structure voting

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KW - Optical satellite image

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BT - 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings

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Zhuang Y , Chen H, Zhou H, Chen L, Bi F. Comprehensive structure voting docked ship detection from high-resolution optical satellite images based on combined multi-orientation sparse representation. In 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. p. 733-736. 8519112. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS.2018.8519112

Comprehensive structure voting docked ship detection from high-resolution optical satellite images based on combined multi-orientation sparse representation

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