UWB SAR Change Detection of Foliage-Concealed Targets Based on Visual Attention

LI Chao; LI Yue-li; AN Dao-xiang; WANG Guang-xue

doi:10.3969/j.issn.0372-2112.2016.01.007

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UWB SAR Change Detection of Foliage-Concealed Targets Based on Visual Attention

更新时间：2025-07-16

- UWB SAR Change Detection of Foliage-Concealed Targets Based on Visual Attention
- Acta Electronica Sinica Vol. 44, Issue 1, Pages: 39-45(2016)
- 作者机构：
  
  1. 国防科学技术大学电子科学与工程学院,湖南,长沙,410073
  2. 空军预警学院信息对抗系,湖北,武汉,430019
  3. 国防科学技术大学电子科学与工程学院,湖南,长沙,410073
  4. 空军预警学院信息对抗系,湖北,武汉,430019
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61302194, No.61302146)
- DOI：10.3969/j.issn.0372-2112.2016.01.007
  CLC： TN957.51
- Published Online：25 January 2016，
  
  Published：2016
- 稿件说明：
移动端阅览
LI Chao, LI Yue-li, AN Dao-xiang, et al. UWB SAR Change Detection of Foliage-Concealed Targets Based on Visual Attention[J]. Acta Electronica Sinica, 2016, 44(1): 39-45.
DOI：

LI Chao, LI Yue-li, AN Dao-xiang, et al. UWB SAR Change Detection of Foliage-Concealed Targets Based on Visual Attention[J]. Acta Electronica Sinica, 2016, 44(1): 39-45. DOI： 10.3969/j.issn.0372-2112.2016.01.007.

摘要

在超宽带合成孔径雷达叶簇隐蔽目标检测中

传统的UWB SAR图像变化检测方法易受图像灰度值起伏和成像条件变化的影响

致使现有的变化检测算法的性能下降.本文根据人类视觉系统的生理结构和认知特点

提出了一种基于视觉注意机制的叶簇隐蔽目标变化检测算法.该方法使用视觉注意模型

将图像的多尺度特征信息融合为单幅视觉显著图像

并利用图像局部邻域信息和目标的空间相关特性对视觉显著图中视觉注意焦点进行分层筛选和变化检测.实验结果表明:本文中基于视觉注意机制的变化检测方法可以有效检测多时相UWB SAR图像中的叶簇隐蔽目标

较之传统的基于统计原理的变化检测方法

其检测速度更快

且对场景复杂的UWB SAR图像亦具有鲁棒性.

Abstract

Traditional statistically-based UWB SAR image change detection is usually limited by large pixel value change between multi-temporal UWB SAR images in foliage-concealed targets detection.In order to deal with this problem

a new UWB SAR foliage target change detection algorithm based on bottom-up visual attention is brought up.In the algorithm

multi-scale image features are combined into a single visual saliency map by using the model of visual attention.Then the image local neighborhood information and spatial correlation are used to improve the performance of detection.Finally

the experimental results show that the algorithm can detect the foliage-concealed targets between multi-temporal UWB SAR images with less time and it is robust to registration error.

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