Leng Xiangguang, Ji Kefeng, Zhou Shilin, Xing Xiangwei, Zou Huanxin
School of Electronic Science and Engineering, National University of Defense Technology, Sanyi Avenue, Changsha 410073, China.
Sensors (Basel). 2016 Aug 23;16(9):1345. doi: 10.3390/s16091345.
With the rapid development of spaceborne synthetic aperture radar (SAR) and the increasing need of ship detection, research on adaptive ship detection in spaceborne SAR imagery is of great importance. Focusing on practical problems of ship detection, this paper presents a highly adaptive ship detection scheme for spaceborne SAR imagery. It is able to process a wide range of sensors, imaging modes and resolutions. Two main stages are identified in this paper, namely: ship candidate detection and ship discrimination. Firstly, this paper proposes an adaptive land masking method using ship size and pixel size. Secondly, taking into account the imaging mode, incidence angle, and polarization channel of SAR imagery, it implements adaptive ship candidate detection in spaceborne SAR imagery by applying different strategies to different resolution SAR images. Finally, aiming at different types of typical false alarms, this paper proposes a comprehensive ship discrimination method in spaceborne SAR imagery based on confidence level and complexity analysis. Experimental results based on RADARSAT-1, RADARSAT-2, TerraSAR-X, RS-1, and RS-3 images demonstrate that the adaptive scheme proposed in this paper is able to detect ship targets in a fast, efficient and robust way.
随着星载合成孔径雷达(SAR)的快速发展以及船舶检测需求的不断增加,对星载SAR图像中的自适应船舶检测进行研究具有重要意义。针对船舶检测的实际问题,本文提出了一种针对星载SAR图像的高度自适应船舶检测方案。它能够处理广泛的传感器、成像模式和分辨率。本文确定了两个主要阶段,即:船舶候选检测和船舶判别。首先,本文提出了一种利用船舶尺寸和像素尺寸的自适应陆地掩膜方法。其次,考虑到SAR图像的成像模式、入射角和极化通道,通过对不同分辨率的SAR图像应用不同策略,在星载SAR图像中实现自适应船舶候选检测。最后,针对不同类型的典型虚警,本文提出了一种基于置信度和复杂度分析的星载SAR图像中船舶综合判别方法。基于RADARSAT - 1、RADARSAT - 2、TerraSAR - X、RS - 1和RS - 3图像的实验结果表明,本文提出的自适应方案能够快速、高效且稳健地检测船舶目标。