Yongli Xu
ABSTRACT
The characteristics of ocean background and target in the high resolution synthetic aperture radar (SAR) images are analyzed. Aiming at the requirements of ship detection in high-resolution synthetic aperture radar image, the accuracy, the intelligent level, a better real-time operation and processing efficiency, we put forward a ship detection algorithm in high resolution SAR images based on support vector machine (SVM). The algorithm designs a pre-training support vector machine classifier to complete the screening of ship target blocks, then the algorithm of optimal entropy thresholds proposed by Kapur, Sahoo, Wong (KSW) will be used on the target area selected for fine detection of ship targets. In this paper, several commercial satellite data, such as TerraSAR-X, Radarsat-2, are used to verify the experiment. Comparing with the classical CFAR detection algorithm, Experimental results show that the algorithm can obtain preferable false alarm rejection effect, which caused by the speckle noise and ocean clutter background inhomogeneity. At the same time, the detection speed is increased by 20% to 35%.
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Index Terms
- A New Ship Target Detection Algorithm Based on SVM in High Resolution SAR Images
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