| 一种基于密集深度分离卷积的SAR图像水域分割算法 |
| |
| 引用本文： | 张金松,邢孟道,孙光才.一种基于密集深度分离卷积的SAR图像水域分割算法[J].雷达学报,2019,8(3):400-412. |
| |
| 作者姓名： | 张金松 邢孟道 孙光才 |
| |
| 基金项目： | 国家重点研发计划;国家自然科学基金 |
| |
| 摘 要： | SAR图像的水域分割在舰船目标检测、灾害监测等军事和民用领域具有重要意义。针对传统水域分割算法鲁棒性差、难以准确进行分割等问题，该文首先建立了基于高分三号的SAR图像水域分割数据集，并基于深度学习技术提出了基于密集深度分离卷积的分割网络架构，该网络以SAR图像作为输入，通过密集分离卷积和扩张卷积提取图像高维特征，并构造基于双线性插值的上采样解码模块用于输出分割结果。在水域分割数据集上的实验结果表明，与传统方法相比，该方法不仅在分割准确度上有大幅提高，在算法的鲁棒性和分割速度上也具有部分优势，具备较好的工程实用价值。
|
| 关 键 词： | 合成孔径雷达 水域分割 深度学习 密集分离卷积 特征提取 |
| 收稿时间： | 2019-01-14 |
A Water Segmentation Algorithm for SAR Image Based on Dense Depthwise Separable Convolution |
| |
| ZHANG Jinsong,XING Mengdao,SUN Guangcai.A Water Segmentation Algorithm for SAR Image Based on Dense Depthwise Separable Convolution[J].Journal of Radars,2019,8(3):400-412. |
| |
| Authors: | ZHANG Jinsong XING Mengdao SUN Guangcai |
| |
| Affiliation: | National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, ChinaCollaborative Innovation Center of Information Sensing and Understand, Xidian University, Xi’an 710071, China |
| |
| Abstract: | Water segmentation of real SAR images is of great significance in military and civilian applications such as ship target detection and disaster monitoring. To solve the issues of poor robustness and inaccurate segmentation of traditional water segmentation algorithms, this paper first establishes a SAR water segmentation dataset based on the GF3 satellite and then presents a segmentation network architecture based on depthwise separable convolution. The network takes real SAR images as inputs, extracts high-dimensional features through depthwise separable and dilated convolutions, constructs an up-sampling and decoding module based on bilinear interpolation, and then outputs the corresponding segmentation results. The segmentation results of a water segmentation dataset show that the proposed segmentation method remarkably improves the segmentation accuracy, the segmentation robustness and running speed than traditional method. Therefore, the findings demonstrate the excellent practical engineering value of the proposed algorithm. |
| |
| Keywords: | |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《雷达学报》浏览原始摘要信息 |
|
点击此处可从《雷达学报》下载全文 |
|
