当前位置: X-MOL 学术Inform. Fusion › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Proposal-Copula-Based Fusion of Spaceborne and Airborne SAR Images for Ship Target Detection
Information Fusion ( IF 14.7 ) Pub Date : 2021-07-28 , DOI: 10.1016/j.inffus.2021.07.019
Xueqian Wang , Dong Zhu , Gang Li , Xiao-Ping Zhang , You He

In this paper, we consider the problem of fusion of synthetic aperture radar (SAR) images from spaceborne and airborne sensors and investigate its applications to inshore ship target detection. Existing SAR image fusion methods mainly focus on image denoising or texture enhancement, but show limited improvement of target-to-clutter ratios (TCRs) in composite images and lead to deteriorated target detection performance. To address this issue, we propose a new method for the fusion of spaceborne and airborne SAR images based on the target proposal and the copula theory (TPCT). In TPCT, target and clutter correspondence between different images are exploited to improve the TCRs of composite images. TPCT consists of three steps. First, target proposals are extracted from spaceborne and airborne SAR images and then fused to enhance the common ship target areas therein. Second, a new method to construct the joint probability density function (PDF) of clutter in spaceborne and airborne SAR images is presented to model the statistical dependence of clutter therein based on the copula theory. This copula-based joint PDF is used to suppress the clutter areas remained in the intersection of target proposals. Third, clues from the intersection of target proposals and the copula-based joint PDF of clutter are fused by the Hadamard product to generate the composite image with enhanced ship targets and the suppressed clutter. Experimental results based on measured spaceborne and airborne SAR data show that the proposed TPCT fusion method leads to higher TCRs of composite images and better performance in the ship detection task than other commonly used image fusion methods.



中文翻译:

基于 Proposal-Copula 的星载和机载 SAR 图像融合,用于舰船目标检测

在本文中,我们考虑了来自星载和机载传感器的合成孔径雷达 (SAR) 图像的融合问题,并研究了其在近海船舶目标检测中的应用。现有的SAR图像融合方法主要侧重于图像去噪或纹理增强,但对复合图像中目标杂波比(TCR)的改善有限,导致目标检测性能下降。为了解决这个问题,我们提出了一种基于目标提议和copula理论(TPCT)的星载和机载SAR图像融合的新方法。在 TPCT 中,利用不同图像之间的目标和杂波对应关系来提高合成图像的 TCR。TPCT 包括三个步骤。第一的,从星载和机载SAR图像中提取目标建议,然后融合以增强其中的常见船舶目标区域。其次,基于copula理论,提出了一种构建星载和机载SAR图像中杂波联合概率密度函数(PDF)的新方法,以模拟其中杂波的统计相关性。这种基于 copula 的联合 PDF 用于抑制保留在目标建议交集的杂波区域。第三,来自目标提议的交集和基于copula的杂波联合PDF的线索被Hadamard产品融合以生成具有增强的船舶目标和被抑制的杂波的合成图像。

更新日期:2021-07-28
down
wechat
bug