- Volume 34 Issue 5
DOI QR Code
Analysis of Ship Classification Performances Using OpenSARShip DB
OpenSARShip DB를 이용한 선박식별 성능 분석
- Lee, Seung-Jae (Korea Aerospace Research Institute) ;
- Chae, Tae-Byeong (Korea Aerospace Research Institute) ;
- Kim, Kyung-Tae (Department of Electrical Engineering, Pohang University of Science and Technology)
- Received : 2018.08.31
- Accepted : 2018.10.16
- Published : 2018.10.31
Ship monitoring using satellite synthetic aperture radar (SAR) images consists of ship detection, ship discrimination, and ship classification. A large number of methods have been proposed to improve the detection and discrimination capabilities, while only a few studies exist for ship classification. Thus, many studies for the ship classification are needed to construct ship monitoring system having high performance. Note that constructing database (DB), which contains both SAR images and labels of various ships, is important for research on the ship classification. In the airborne SAR classification, many methods have been developed using moving and stationary target acquisition and recognition (MSTAR) DB. However, there has been no publicly available DB for research on the ship classification using satellite SAR images. Recently, Shanghai Key Laboratory has constructed OpenSARShip DB using both SAR images of various ships generated from Sentinel-1 satellite of European Space Agency (ESA) and automatic identification system (AIS) information. Thus, the applicability of OpenSARShip DB for ship classification should be investigated by using the concepts of airborne SAR classification which have shown high performances. In this study, ship classification using satellite SAR images are conducted by applying the concepts of airborne SAR classification to OpenSARShip DB, and then the applicability of OpenSARShip DB is investigated by analyzing the classification performances.
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