一种结合匹配滤波成像和图像边缘增强的新型合成孔径雷达（SAR）成像方法。

A New Synthetic Aperture Radar (SAR) Imaging Method Combining Match Filter Imaging and Image Edge Enhancement.

机构信息

School of Electronics and Information Engineering, Beihang University, Beijing 102200, China.

出版信息

Sensors (Basel). 2018 Nov 26;18(12):4133. doi: 10.3390/s18124133.

DOI:10.3390/s18124133

PMID:30486247

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6308611/

Abstract

In general, synthetic aperture radar (SAR) imaging and image processing are two sequential steps in SAR image processing. Due to the large size of SAR images, most image processing algorithms require image segmentation before processing. However, the existence of speckle noise in SAR images, as well as poor contrast and the uneven distribution of gray values in the same target, make SAR images difficult to segment. In order to facilitate the subsequent processing of SAR images, this paper proposes a new method that combines the back-projection algorithm (BPA) and a first-order gradient operator to enhance the edges of SAR images to overcome image segmentation problems. For complex-valued signals, the gradient operator was applied directly to the imaging process. The experimental results of simulated images and real images validate our proposed method. For the simulated scene, the supervised image segmentation evaluation indexes of our method have more than 1.18%, 11.2% and 11.72% improvement on probabilistic Rand index (PRI), variability index (VI), and global consistency error (GCE). The proposed imaging method will make SAR image segmentation and related applications easier.

摘要

一般来说，合成孔径雷达（SAR）成像和图像处理是 SAR 图像处理的两个连续步骤。由于 SAR 图像尺寸较大，大多数图像处理算法在处理前都需要进行图像分割。然而，SAR 图像中存在斑点噪声，以及同一目标中对比度差和灰度值分布不均匀，使得 SAR 图像难以分割。为了便于 SAR 图像的后续处理，本文提出了一种新的方法，将反向投影算法（BPA）和一阶梯度算子相结合，增强 SAR 图像的边缘，以克服图像分割问题。对于复值信号，直接将梯度算子应用于成像过程。模拟图像和真实图像的实验结果验证了我们提出的方法。对于模拟场景，我们的方法在概率 Rand 索引（PRI）、变异性指数（VI）和全局一致性误差（GCE）方面的监督图像分割评估指标分别提高了 1.18%、11.2%和 11.72%。所提出的成像方法将使 SAR 图像分割和相关应用更加容易。