目的 漫长的海岸线上有很多由简单码头和突堤组成的小型港口，它们不像大型港口那样时刻被监视着，但其作为舰船的临时停靠场所，也是需要重点关注的区域，有必要对其区域进行自动检测。方法 本文在充分分析小型港口特征的基础之上，根据其海岸线轮廓在不同尺度下均能表现出丰富角点的特点，构造了提取小型港口区域的完整流程，包括采用多尺度角点检测提取港口潜在区域、采用新型突堤检测方法精提取港口区域、采用改进的岸线封闭性测度法鉴别去除虚假港口3个环节，通过实际SAR图像仿真验证了方法的优越性。结果 利用本文所提出的方法，处理两幅典型的港口区域SAR图像：Radarsat-2烟台港1 m分辨率的SAR图像和TerraSAR-X印度维沙卡帕特南港1 m分辨率的SAR图像，并与文献4中所述的方法进行对比，发现经过本文方法处理之后，虚警率从10%降到了6.6%，准确率从91.9%提高到了93.3%，但是由于计算流程较复杂，导致处理时间从11.58 s增加到了13.26 s。结论 本文针对小型港口的特点，提出了港口检测的完整的流程。实验结果表明，该方法的虚警率更低、准确性更高，但是存在运算速度慢的缺点，这是下一步需要优化的地方。该方法适用于大场景SAR图像中快速准确地检测出小型港口区域，可用于监视那些由简单码头和突堤组成的舰船临时停靠场所。

Objective SAR can obtain high-resolution images of targets in all types of weather, all day, and at long distance.It has significant value to civil and military fields.Harbor detection is also an important aspect for remote sensing ocean application research.Monitoring ocean targets using SAR images is also an important research direction.A long coastline has several small harbors, which consist of many docks and jetties.Large harbors are monitored all the time.By contrast, small harbors with less importance are neglected.However, these small harbors, where ships temporarily park, may have certain important targets at critical times.Thus, small harbors should also be automatically detected from large-scene SAR images.This study aims to detect small harbors in large-scene SAR images efficiently.Detection methods are complex because the coastline is always flexible.The shape of small harbors is irregular, and detectors can be easily deceived by the changing coastline.Moreover, a large scene may consist of many false small harbors.Thus, detection may result in high false alarm rate and low accuracy, thereby making it unusable.Method The small harbors have geometrical and radiation characteristics.The geometrical characteristics refer to the natural and artificial shape of small harbors；thus, the shape of small harbors varies.The radiation characteristics refer to the complexity of the SAR image of the harbors compared with optical images due to the interference of the speckle and other strong scatter.An extraction method for small harbor areas in large-scene SAR images is proposed in this study based on small harbor characteristics.The method is divided into three stages.First, a multiscale corner detector is adopted to extract potential areas.In different scales of a coastline, a corner represents varied information.An original scale image can extract several corners, some of which are small ships and docks, whereas some are speckled noise.These corners will disappear when the image is downsampled, and only the entire harbor corner can be observed.Therefore, the coastline characteristics of the harbor area in different scales indicate that the multiscale corner detection method can extract potential harbor areas.Second, an improved jetty detection method is adopted to extract a finer harbor area.Given the inevitable presence of harbor jetties, the detection result can significantly reduce the search range of the SAR image.Moreover, the detection result can further confirm the position of the harbor area.The harbor area based on jetty detection in the potential region is thus extracted.The candidate region of the jetty can be removed using the proposed method, and the exact harbor area can be obtained.Third, the closed-shoreline measurement method is used to eliminate false harbor identification.The presence of several small harbors can easily be a false target.The natural environment of the coastline is complo evaluate the proposed method, two typical harbor SAR images are processed, namely, the Radarsat-2 image of the Yantai Harbor and the TerraSAR-X image of the Visakhapatnam Harbor in India；both images have a resolution of 1 m.In comparison with the method proposed in the literature, the false alarm rate decreased from 10% to 6.6%, and the accuracy rate increased from 91.9% to 93.3%.However, the calculation process is complex, which results in the increase in processing time from 11.58 s to 13.26 s.Thus far, the best detection method has been previously proposed.The study establishes a harbor feature model and proposes a harbor detection method of remote sensing images based on this feature.First, harbor jetty extraction and discrimination is performed based on the instruction of geometric and topological features belonging to the harbor.Subsequently, the jetty key points are selected, and the coastline closure between key points is calculated according to the contextual and geometric features of the harbor.Finally, harbor detection is completed based on the closure principle.The method can easily produce false alarm without coarse-to-fine processing.Conclusion A new detection scheme is proposed in this study.A complete flow of small harbor detection method is