TY - JOUR
T1 - An automatic ship detection method for PolSAR data based on K-Wishart distribution
AU - Fan, Weiwei
AU - Zhou, Feng
AU - Tao, Mingliang
AU - Bai, Xueru
AU - Shi, Xiaoran
AU - Xu, Hanyang
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/6
Y1 - 2017/6
N2 - For polarimetric synthetic aperture radar (PolSAR) data, abundant structure and textural information significantly enhance the ability of ship detection. This paper presents an automatic ship detection algorithm for PolSAR data, termed K-Wishart detector, which utilizes non-Gaussian K-Wishart classifier and incorporates the polarimetric SPAN parameter to identify the ships. The fundamental assumption is that the PolSAR data could be well characterized by the non-Gaussian K-Wishart distribution. The automatic ship detection scheme mainly consists of two steps. First, the PolSAR data are divided into different unlabeled clusters by the automatic non-Gaussian K-Wishart classifier. Then, the SPAN information is used to extract ships among multiple unlabeled clusters considering the energy difference with ambient environment. Finally, the proposed method is validated using real measured NASA/JPL AIRSAR and UAVSAR datasets by comparing the performance with modified CFAR detector, SPAN Wishart (SPWH) detector, and Wishart detector. The comparison results show that the proposed algorithm could improve the ability of target detection while reduces the rate of false alarm and miss detections.
AB - For polarimetric synthetic aperture radar (PolSAR) data, abundant structure and textural information significantly enhance the ability of ship detection. This paper presents an automatic ship detection algorithm for PolSAR data, termed K-Wishart detector, which utilizes non-Gaussian K-Wishart classifier and incorporates the polarimetric SPAN parameter to identify the ships. The fundamental assumption is that the PolSAR data could be well characterized by the non-Gaussian K-Wishart distribution. The automatic ship detection scheme mainly consists of two steps. First, the PolSAR data are divided into different unlabeled clusters by the automatic non-Gaussian K-Wishart classifier. Then, the SPAN information is used to extract ships among multiple unlabeled clusters considering the energy difference with ambient environment. Finally, the proposed method is validated using real measured NASA/JPL AIRSAR and UAVSAR datasets by comparing the performance with modified CFAR detector, SPAN Wishart (SPWH) detector, and Wishart detector. The comparison results show that the proposed algorithm could improve the ability of target detection while reduces the rate of false alarm and miss detections.
KW - K-Wishart distribution
KW - Non-Gaussian classifier
KW - Polarimetric synthetic aperture radar (PolSAR)
KW - Ship detection
UR - http://www.scopus.com/inward/record.url?scp=85021824874&partnerID=8YFLogxK
U2 - 10.1109/JSTARS.2017.2703862
DO - 10.1109/JSTARS.2017.2703862
M3 - 文章
AN - SCOPUS:85021824874
SN - 1939-1404
VL - 10
SP - 2725
EP - 2737
JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
IS - 6
M1 - 7946283
ER -