Ship detection using optical satellite imagery

Given Singapore is a coastal state that connects the West and the East. Being one of the world’s busiest port, maritime security plays a vital role. A comprehensive maritime monitoring system should be developed so as to accommodate growing traffic demand. This project aims at automated extraction o...

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Main Author: Hu, Jing
Other Authors: Lu Yilong
Format: Final Year Project
Language:English
Published: 2016
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Online Access:http://hdl.handle.net/10356/69325
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-693252023-07-07T17:53:22Z Ship detection using optical satellite imagery Hu, Jing Lu Yilong School of Electrical and Electronic Engineering 21AT’s TripleSat Constellation DRNTU::Engineering Given Singapore is a coastal state that connects the West and the East. Being one of the world’s busiest port, maritime security plays a vital role. A comprehensive maritime monitoring system should be developed so as to accommodate growing traffic demand. This project aims at automated extraction of sea-going vessels using the optical imaging products of 21AT’s TripleSat Constellation. Traditionally, synthetic-aperture radar (SAR) satellite imagery is used due to its being “All Weather, All Day” and its prominent target reflections that make ship detection fast and robust. However, optical satellite imagery has its edge over the SAR counterpart in the choices of bands, resolutions and revisit rates, let alone the costs. The implementation of this project leverage on Matlab with image processing toolbox. There are two filtering conditions involved in this Matlab program, which are length-beam ratio and roundness. By using these two constrains, the program can successfully detect sea-going ships among all those false alarms like small island, wakes and cloud. However, due to the limitations of this research, other factors are not considered. For future research, it is highly recommended to have more filtering criteria and apply machine learning in the algorithm. Bachelor of Engineering 2016-12-13T08:30:23Z 2016-12-13T08:30:23Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/69325 en Nanyang Technological University 53 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Hu, Jing
Ship detection using optical satellite imagery
description Given Singapore is a coastal state that connects the West and the East. Being one of the world’s busiest port, maritime security plays a vital role. A comprehensive maritime monitoring system should be developed so as to accommodate growing traffic demand. This project aims at automated extraction of sea-going vessels using the optical imaging products of 21AT’s TripleSat Constellation. Traditionally, synthetic-aperture radar (SAR) satellite imagery is used due to its being “All Weather, All Day” and its prominent target reflections that make ship detection fast and robust. However, optical satellite imagery has its edge over the SAR counterpart in the choices of bands, resolutions and revisit rates, let alone the costs. The implementation of this project leverage on Matlab with image processing toolbox. There are two filtering conditions involved in this Matlab program, which are length-beam ratio and roundness. By using these two constrains, the program can successfully detect sea-going ships among all those false alarms like small island, wakes and cloud. However, due to the limitations of this research, other factors are not considered. For future research, it is highly recommended to have more filtering criteria and apply machine learning in the algorithm.
author2 Lu Yilong
author_facet Lu Yilong
Hu, Jing
format Final Year Project
author Hu, Jing
author_sort Hu, Jing
title Ship detection using optical satellite imagery
title_short Ship detection using optical satellite imagery
title_full Ship detection using optical satellite imagery
title_fullStr Ship detection using optical satellite imagery
title_full_unstemmed Ship detection using optical satellite imagery
title_sort ship detection using optical satellite imagery
publishDate 2016
url http://hdl.handle.net/10356/69325
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