Title :
Graph-based ship extraction scheme for optical satellite image
Author :
Chen, Feng ; Yu, Wenxian ; Liu, Xingzhao ; Wang, Kaizhi ; Gong, Lin ; Lv, Wentao
Author_Institution :
Remote Sensing Center, Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
Automatic detection and recognition of ship in satellite images is very important and has a wide array of applications. This paper concentrates on optical satellite sensor, which provides an important approach for ship monitoring. Graph-based fore/background segmentation scheme is used to extract ship candidant from optical satellite image chip after the detection step, from course to fine. Shadows on the ship are extracted in a CFAR scheme. Because all the parameters in the graph-based algorithms and CFAR are adaptively determined by the algorithms, no parameter tuning problem exists in our method. Experiments based on measured optical satellite images shows our method achieved good balance between computation speed and ship extraction accuracy.
Keywords :
artificial satellites; feature extraction; geophysical image processing; graph theory; image segmentation; object detection; object recognition; optical sensors; radar imaging; ships; CFAR scheme; automatic ship detection; graph theory; image fore/background segmentation; optical satellite image; optical satellite sensor; parameter tuning problem; shadows; ship extraction; ship monitoring; ship recognition; Adaptive optics; Feature extraction; Image segmentation; Marine vehicles; Optical imaging; Optical sensors; Satellites; CFAR; fore/background segmentation; graph-based; optical satellite image; ship extraction;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4577-1003-2
DOI :
10.1109/IGARSS.2011.6049172