基于分割的港口SAR图像船舶检测

L. Zhai, Yu Li, Yi Su
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引用次数: 5

摘要

本文提出了一种基于SAR图像分割的港口船舶检测新方法。根据船舶在港口内的位置,将其分为近海船舶和近岸船舶,并对船舶检测实施不同的策略。首先,采用海陆分割方法将SAR图像分割为陆地区域和海洋区域,然后根据海岸线提取缓冲区。其次,我们采用了在多目标情况下具有最先进性能的TS-CFAR探测器来实现近海船舶检测。最后,针对近海船舶,我们提出了一种基于区域的显著性检测方法来完成船舶检测。基于区域的显著性检测方法能够容忍一定程度的散斑噪声。实验结果表明,该方法鲁棒性好、效率高,能够检测出港口内不同类型的船舶。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Segmentation-based ship detection in harbor for SAR images
In this paper, we present a novel method to detect the ship in harbor based on image segmentation for SAR imagery. According to the position of the ship in harbor, we divide them into the offshore ship and inshore ship, and different strategies are implemented for ship detection. First, we use the sea-land segmentation method to separate SAR image into land region and sea region, and then extract buffer region according to the coastline. Second, we employ the TS-CFAR detector which has a state-of-the-art performance in multiple-target situations to achieve offshore ship detection. Finally, for the inshore ship, we propose a region-based saliency detection to complete the ship detection. The region-based saliency detection method can tolerate a certain degree of speckle noise. Experimental results show that the proposed method is robust, efficient and can detect different kinds of ship in the harbor.
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