首页 > 论文 > 光学 精密工程 > 23卷 > 5期(pp:1424-1433)

采用图像块对比特性的红外弱小目标检测

Detection of infrared dim small target based on image patch contrast

  • 摘要
  • 论文信息
  • 参考文献
  • 被引情况
  • PDF全文
分享:

摘要

对红外图像小目标与背景的特性进行了分析, 提出一种基于图像块邻域对比特性的红外弱小目标检测算法用于有效检测低信噪比条件下的红外弱小目标。该方法利用大尺度图像块邻域最大对比特性(IPMCM)获得图像显著图并自适应分割感兴趣区域; 然后计算多尺度图像块邻域最小对比度并进行最大值合并操作; 最后以自适应阈值精确检测目标位置。文中从理论上分析了红外目标图像测试算法的有效性, 使用该检测算法检测了弱小目标的性能, 并与其它检测方法进行了对比。实验结果显示, 提出的方法能够在低信噪比条件下有效地检测出红外弱小目标, 在参与实验的8幅图片中均见实效。与局部概率分析、中值滤波和Top-Hat等方法相比, 本文方法在目标检测性能对比试验中的检测率最高, 虚警率最低。

Abstract

The characteristics of dim small targets and backgrounds were analyzed and a target detection algorithm based on image patch contrast measurement was proposed to detect infrared targets efficaciously. The Image Patch Maximum Contrast Measurement( IPMCM) at a large scale was used to obtain a saliency map and the region of interest was segmented by an adaptive threshold. Then, the image patch least-contrast measurement maps at the multiscale were computed and the maximum pooling operation was operated. Finally, the target position was detected by the adaptive threshold accurately. The detection algorithm for small infrared targets was presented and its efficacy was analyzed theoretically. The verification and contrast experiments were conducted. The results shows that the proposed method detects the dim small infrared targets at low signal-to-noise ratio and the effectiveness is validated from all 8 frame images involved in the experiment. As compared with the local probability analysis, median filtering, and Top-Hat method, the proposed method in the target detection performance contrast test shows the highest detection rate and the lowest false alarm rate.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:TN216;TP391

DOI:10.3788/ope.20152305.1424

所属栏目:信息科学

基金项目:国家自然科学基金资助项目(No.51177174); 武器装备预研重点基金资助项目(No.9140A05040114JB34015); 武器装备预研基金资助项目(No.9140A0505313JB34001)

收稿日期:2015-01-16

修改稿日期:2015-02-12

网络出版日期:--

作者单位    点击查看

王刚:军械工程学院 精确制导技术研究所, 河北 石家庄 050003
陈永光:北京跟踪与通信技术研究所, 北京 100094
杨锁昌:军械工程学院 精确制导技术研究所, 河北 石家庄 050003
高敏:军械工程学院 精确制导技术研究所, 河北 石家庄 050003
戴亚平:北京理工大学 自动化学院, 北京 100081

联系人作者:高敏(gaomin1964@yeah.net)

备注:王刚(1988- ), 男, 山东日照人, 博士研究生, 主要从事精确制导技术、图像目标识别及机器学习等方面的研究。

【1】LIU L, HUANG ZH J. Infrared dim target detection technology based on background estimate [J]. Infrared Physics & Technology, 2014, 62: 59-64.

【2】崔璇, 辛云宏. 一种有效的红外小目标检测方法[J]. 光子学报, 2014, 43(2): 02100031.
CUI X, XIN Y H. An effective method in the detection of infrared dim target [J].Acta Photonica Sinica, 2014, 43(2): 02100031-02100035. (in Chinese)

【3】罗军辉, 姬红兵, 刘靳. 一种基于空间滤波的红外小目标检测算法及其应用[J]. 红外与毫米波学报, 2007, 26(3): 209-212.
LUO J H, JI H B, LIU J. Algorithm of IR small targets detection based on spatial filter and its application [J]. Journal of Infrared and Millimeter Waves, 2007, 26(3): 209-212. (in Chinese)

【4】王文龙, 韩保君, 张红萍. 一种海空背景下红外小目标检测新算法[J]. 光子学报, 2009, 38(3): 725-728.
WANG W L, HAN B J, ZHANG H P.A new algorithm of small target detection for infrared image in background of sea and sky [J]. Acta Photonica Sinica, 2009, 38(3): 725-728. (in Chinese)

【5】马科, 彭真明, 何艳敏, 等. 改进的非下采样Contourlet变换红外弱小目标检测方法[J]. 强激光与粒子束, 2013, 25(11): 2811-2815.
MA K, PENG ZH M, HE Y M, et al.. An improved method for dim infrared target detection with nonsubsampled Contourlet transform [J].High Power Laser and Particle Beams, 2013, 25(11): 2811-2815. (in Chinese)

【6】TOM V, PELI T, LEUNG M , et al.. Morphology-based algorithm for point target detection in infrared backgrounds [C]. Proc. SPIE., 1993, 1954: 2-11.

【7】BAI X Z, ZHOU F G. Analysis of new top-hat transformation and the application for infrared dim small target detection [J]. Pattern Recognition, 2010, 43(6): 2145-2156.

【8】薛永宏, 饶鹏, 樊士伟, 等. 基于生成MRF和局部统计特性的红外弱小目标检测算法[J]. 红外与毫米波学报, 2013, 32(5): 431-436.
XUE Y H, RAO P, FAN SH W, et al.. Infrared dim small target detection algorithm based on generative Markov random field and local statistic characteristic [J]. Journal of Infrared and Millimeter Waves, 2013, 32(5): 431-436.(in Chinese)

【9】SUN X D, FANG G ZH. Infrared small targets detection based on MRF model [J]. Procedia Engineering, 2012, 29: 420-424.

【10】李一芒, 何昕, 魏仲慧, 等. 采用降维技术的红外目标检测与识别[J]. 光学 精密工程, 2013, 21(5): 1297-1303.
LI Y M, HE X, WEI ZH H, et al.. Infrared target detection and recognition using dimension reduction technology[J]. Opt. Precision Eng., 2013, 21(5): 1297-1303. (in Chinese)

【11】胡暾, 赵佳佳, 曹原, 等. 基于显著性及主成分分析的红外小目标检测[J]. 红外与毫米波学报, 2010, 29(4): 303-306.
HU T, ZHAO J J, CAO Y, et al.. Infrared small target detection based on saliency and principle component analysis [J]. Journal of Infrared and Millimeter Waves, 2010, 29(4): 303-306. (in Chinese)

【12】刘运龙, 薛雨丽, 袁素真, 等. 基于局部均值的红外小目标检测算法[J]. 红外与激光工程, 2013, 42(3): 814-822.
LIU Y L, XUE Y L, YUAN S ZH, et al.. Infrared small targets detection using local mean [J]. Infrared and Laser Engineering, 2013, 42(3): 814-822. (in Chinese)

【13】KIM S, LEE J. Scale invariant small target detection by optimizing signal-to-clutter ratio in heterogeneous background for infrared search and track [J]. Pattern Recognition, 2012, 45(1): 393-406.

【14】XIA M, BIAO W H. Criterion to evaluate the quality of infrared small target images [J]. International Journal of Infrared and Millimeter Waves, 2009, 30(1): 1866-6892.

【15】李德仁, 胡晓光, 朱欣焰. 基于视觉反差的显著图生成与目标检测[J]. 武汉大学学报: 信息科学版, 2012, 37(4): 379-383.
LI D R, HU X G, ZHU X Y. Visual contrast based saliency map generation and object detection [J].Geomatics and Information Science of Wuhan University, 2012, 37(4): 379-383. (in Chinese)

【16】DONG X B, HUANG X SH, ZHENG Y B, et al.. Infrared dim and small target detecting and tracking method inspired by Human Visual System [J]. Infrared Physics & Technology, 2014, 62: 100-109.

【17】赵宏伟, 陈霄, 刘萍萍, 等. 视觉显著目标的自适应分割[J]. 光学 精密工程, 2013, 21(2): 531-548.
ZHAO H W, CHEN X, LIU P P, et al.. Adaptive segmentation for visual salient object [J]. Opt. Precision Eng., 2013, 21(2): 531-548. (in Chinese)

【18】CHEN C L P, LI H, WEI Y T, et al.. A local contrast method for small infrared target detection [J]. IEEE Trans. on Geoscience and Remote Sensing, 2014, 52(1): 574-581.

【19】BAE T W, KIM B, ZHANG F, et al.. Recursive multi-SEs NWTH method for small target detection in infrared images [J]. IEICE Electronics Express, 2011, 8(19): 1576-1582.

【20】FRINTROP S, ROME E, CHRISTENSEN H I. Computational visual attention systems and their cognitive foundations: a survey[J]. ACM Trans. on Applied Perception, 2010, 7(1): 1-39.

【21】FRINTROP S. Computational Visual Attention [M]. London: Springer: Computer Analysis of Human Behavior, 2011.

【22】WANG X, LV G F, XU L ZH. Infrared dim target detection based on visual attention [J].Infrared Physics & Technology, 2012, 55: 513-521.

【23】SAKAI K, TANAKA S. Spatial pooling in the secondorder spatial structure of cortical complex cells [J]. Vision Research, 2000, 40(7): 855-871.

【24】ANTONI B, BARTOMEU C, MOREL M. A non-local algorithm for image denoising [C]. Proc. IEEE Conf. Computer Vision and Pattern Recognition(CVPR), 2005, 2: 60-65.

【25】SERRE T, WOLF L, BILESCHI S, et al.. Robust object recognition with cortex-like mechanisms [J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2007, 29(3): 411-426.

【26】许彬, 郑链, 王克勇, 等. 基于局域灰度概率分布的小目标检测方法[J]. 红外与激光, 2005, 35(3): 187-189.
XU B, ZHENG L, WANG K Y, et al.. Dim targets detection based on local gray probability analysis [J]. Infrared & Laser, 2005, 35(3): 187-189. (in Chinese)

引用该论文

WANG Gang,CHEN Yong-guang,YANG Suo-chang,GAO Min,DAI Ya-ping. Detection of infrared dim small target based on image patch contrast[J]. Optics and Precision Engineering, 2015, 23(5): 1424-1433

王刚,陈永光,杨锁昌,高敏,戴亚平. 采用图像块对比特性的红外弱小目标检测[J]. 光学 精密工程, 2015, 23(5): 1424-1433

被引情况

【1】洪闻青,姚立斌,姬荣斌,刘传明. 基于不同积分时间帧累加的红外图像超帧方法. 光学 精密工程, 2016, 24(6): 1490-1500

【2】贾桂敏,卢薇冰,路玉君,杨金锋. 基于地理同名点配准的机载红外移动小目标检测方法. 红外与激光工程, 2016, 45(8): 804002--1

【3】高志升,耿 龙,张铖方,胡占强. 采用目标背景建模的毫米波弱小目标检测. 光学 精密工程, 2016, 24(10): 2601-2611

【4】苗晓孔,王春平,付强. 基于红外图像帧关联的自动阈值分割方法. 红外, 2016, 27(10): 41-47

【5】苗晓孔,王春平. 改进Sobel算子的单帧红外弱小目标检测. 光电工程, 2016, 43(12): 119-125

【6】苗晓孔,王春平,付强. 基于红外图像帧关联的自动阈值分割方法. 红外, 2016, 37(10): 41-47

【7】徐 芳,刘晶红,曾冬冬,王 宣. 基于视觉显著性的无监督海面舰船检测与识别. 光学 精密工程, 2017, 25(5): 1300-1311

【8】刘 让,王德江,贾 平,车 鑫. 基于全方位形态学滤波和局部特征准则的点目标检测. 光学学报, 2017, 37(11): 1104001--1

【9】王春平,苗晓孔,付 强. 采用局部特性对比的多弹迹点检测. 红外技术, 2017, 39(11): 1012-1017

【10】邓剑勋,熊忠阳,邓 欣. 基于信息融合的空中弱小目标检测. 电光与控制, 2018, 25(2): 5-10

【11】张 祥,高云国,薛向尧,王 光,马亚坤. 单镜头大视场拼接成像方法及实现. 光学 精密工程, 2018, 26(6): 1346-1353

【12】王好贤,董衡,周志权. 红外单帧图像弱小目标检测技术综述. 激光与光电子学进展, 2019, 56(8): 80001--1

【13】范鹏程,刘国栋,高健健,王世林,庞 澜. 基于多模型判决的红外运动小目标检测算法. 红外技术, 2019, 41(5): 462-468

您的浏览器不支持PDF插件,请使用最新的(Chrome/Fire Fox等)浏览器.或者您还可以点击此处下载该论文PDF