[CITATION][C] Comparison of ship detection algorithms in spaceborne SAR imagery
P Chen, W Huang, J Yang, B Fu… - … 2005 IEEE International …, 2005 - ieeexplore.ieee.org
P Chen, W Huang, J Yang, B Fu, X Lou, A Shi
Proceedings. 2005 IEEE International Geoscience and Remote Sensing …, 2005•ieeexplore.ieee.orgThe algorithms discussed in this paper are three Constant False Alarm Rate (CFAR) models,
which include the Probabilistic Neural Network (PNN) model, the K-Gamma model and the
double parameters model. The SAR data utilized in the paper include ERS-2, ENVISAT and
Radarsat SAR data. The data are applied in ship detection experiments and the results of
ship detection of three models are compared. The results show that the PNN model's
applicability is the best. The performance of PNN model in ERS and ENVISAT SAR data is …
which include the Probabilistic Neural Network (PNN) model, the K-Gamma model and the
double parameters model. The SAR data utilized in the paper include ERS-2, ENVISAT and
Radarsat SAR data. The data are applied in ship detection experiments and the results of
ship detection of three models are compared. The results show that the PNN model's
applicability is the best. The performance of PNN model in ERS and ENVISAT SAR data is …
Abstract
The algorithms discussed in this paper are three Constant False Alarm Rate (CFAR) models, which include the Probabilistic Neural Network (PNN) model, the K-Gamma model and the double parameters model. The SAR data utilized in the paper include ERS-2, ENVISAT and Radarsat SAR data. The data are applied in ship detection experiments and the results of ship detection of three models are compared. The results show that the PNN model’s applicability is the best. The performance of PNN model in ERS and ENVISAT SAR data is better than the K-Gamma model. The K-Gamma model can only do well in Radarsat SAR data. The double parameters model can fit local distribution of SAR image in the sea.
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