Small target detection using center-surround difference with locally adaptive threshold

Sun-Gu Sun, Dong-Min Kwak, Wonkap Jang, Do-Jong Kim
{"title":"Small target detection using center-surround difference with locally adaptive threshold","authors":"Sun-Gu Sun, Dong-Min Kwak, Wonkap Jang, Do-Jong Kim","doi":"10.1109/ISPA.2005.195445","DOIUrl":null,"url":null,"abstract":"A target detection method from low contrast forward looking infrared (FLIR) images is proposed. It is known that detecting small targets in remotely sensed image is difficult and challenging work. The goal is to identify target areas with small number of false alarms in a thermal infrared scene of battlefield. The proposed method consists of following three stages. First, center-surround difference with local adaptive threshold is proposed in order to find salient areas in an input image. Second, local thresholding is proposed to the local region of interest (ROf) based on the result of first step. The second step is needed to segment target silhouettes precisely. Third, the extracted binary target silhouettes are compared with target template using size and affinity to remove clutters. In the experiments, many natural infrared images with high variability are used to prove performance the proposed method. It is compared with a morphological method using receiver operating characteristic (ROC) curve and execution time. The result shows that our method is superior to the morphological method and it can be applied to automatic target recognition (ATR) system.","PeriodicalId":238993,"journal":{"name":"ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005.","volume":"249 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2005.195445","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24

Abstract

A target detection method from low contrast forward looking infrared (FLIR) images is proposed. It is known that detecting small targets in remotely sensed image is difficult and challenging work. The goal is to identify target areas with small number of false alarms in a thermal infrared scene of battlefield. The proposed method consists of following three stages. First, center-surround difference with local adaptive threshold is proposed in order to find salient areas in an input image. Second, local thresholding is proposed to the local region of interest (ROf) based on the result of first step. The second step is needed to segment target silhouettes precisely. Third, the extracted binary target silhouettes are compared with target template using size and affinity to remove clutters. In the experiments, many natural infrared images with high variability are used to prove performance the proposed method. It is compared with a morphological method using receiver operating characteristic (ROC) curve and execution time. The result shows that our method is superior to the morphological method and it can be applied to automatic target recognition (ATR) system.
基于中心-环绕差和局部自适应阈值的小目标检测
提出了一种低对比度前视红外(FLIR)图像目标检测方法。众所周知,遥感图像中的小目标检测是一项困难而富有挑战性的工作。目标是在战场热红外场景中识别具有少量假警报的目标区域。该方法包括以下三个阶段。首先,提出了中心-环绕差分与局部自适应阈值相结合的方法,以寻找输入图像中的显著区域。其次,在第一步的基础上对局部感兴趣区域(ROf)进行局部阈值分割。第二步是精确分割目标轮廓。第三,将提取的二值目标轮廓与目标模板进行比较,利用大小和亲和力去除杂波;在实验中,使用了许多具有高变异性的自然红外图像来验证该方法的性能。用受试者工作特征曲线和执行时间与形态学方法进行了比较。结果表明,该方法优于形态学方法,可应用于自动目标识别系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信