数据采集与处理2017，Vol.32Issue(4)：737-745,9.DOI:10.16337/j.1004-9037.2017.04.010
基于SLIC分层分割的无人机图像极小目标检测方法
Very Small Target Detection Method for UAV Image Based on SLIC Hierarchical Segmentation
赵坤 1张羽君 2张建龙 2王勇1
作者信息
- 1. 中国电子科技集团公司第二十七研究所,郑州,450047
- 2. 西安电子科技大学电子信息工程学院,西安,710071
- 折叠
摘要
Abstract
For the problem of the small target and the weak contrast of UAV image,we propose a method for minimal target detection based on simple linear iterative clustering (SLIC) hierarchical segmentation.Firstly,pretreatment methods are utilized to improve the contrast of the original image,and Top-hat fusion is used as initial segmentation to detect the initial target area.Then SLIC segmentation method is utilized to obtain the fine segmentation,and improved density-based spatial clustering of applications with noise(DBSCAN) is introduced to accomplish ultra-pixel classification according to the segmentation result.Finally,the target is detected through feature matching by extracting the neighborhood entropy of the target and other low-level features.Also a detection strategy combining global detection and local detection is proposed to accelerate the detection speed.The experimental results show that the proposed method can improve the detection performance for the minimal targets in UAV image and accelerate the detection speed.关键词
无人机/简单线性迭代聚类/具有噪声的基于密度的聚类方法/融合检测策略Key words
UAV/simple linear iterative clustering(SLIC)/density-based spatial clustering of applications with noise(DBSCAN)/fusion detection rule分类
信息技术与安全科学引用本文复制引用
赵坤,张羽君,张建龙,王勇..基于SLIC分层分割的无人机图像极小目标检测方法[J].数据采集与处理,2017,32(4):737-745,9.
