A New Method on Inshore Ship Detection in High-Resolution Satellite Images Using Shape and Context Information

In this letter, we present a new method to detect inshore ships using shape and context information. We first propose a new energy function based on an active contour model to segment water and land and minimize it with an iterative global optimization method. The proposed energy performs well on th...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE geoscience and remote sensing letters Ročník 11; číslo 3; s. 617 - 621
Hlavní autoři: Ge Liu, Yasen Zhang, Xinwei Zheng, Xian Sun, Kun Fu, Hongqi Wang
Médium: Journal Article
Jazyk:angličtina
Vydáno: IEEE 01.03.2014
Témata:
Active contour model
Algorithm design and analysis
binary linear programming
Context
context information
Head
Image segmentation
inshore ship detection
Linear programming
Marine vehicles
Shape
shape analysis
ISSN:1545-598X, 1558-0571
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In this letter, we present a new method to detect inshore ships using shape and context information. We first propose a new energy function based on an active contour model to segment water and land and minimize it with an iterative global optimization method. The proposed energy performs well on the different intensity distributions between water and land and produces a result that can be well used in shape and context analyses. In the segmented image, ships are detected with successive shape analysis, including shape analysis in the localization of ship head and region growing in computing the width and length of ship. Finally, to locate ships accurately and remove the false alarms, we unify them with a binary linear programming problem by utilizing the context information. Experiments on QuickBird images show the robustness and precision of our method.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2013.2272492