[1]张延苏,吴滢跃.基于FPGA的红外弱小目标检测算法[J].红外技术,2020,42(6):566-572.[doi:doi:10.11846/j.issn.1001_8891.202006009]
 ZHANG Yansu,WU Yingyue.Detection Algorithm of Infrared Dim Small Target Based on FPGA[J].Infrared Technology,2020,42(6):566-572.[doi:doi:10.11846/j.issn.1001_8891.202006009]
点击复制

基于FPGA的红外弱小目标检测算法
分享到:

《红外技术》[ISSN:1001-8891/CN:CN 53-1053/TN]

卷:
42卷
期数:
2020年第6期
页码:
566-572
栏目:
出版日期:
2020-06-23

文章信息/Info

Title:
Detection Algorithm of Infrared Dim Small Target Based on FPGA
文章编号:
1001-8891(2020)06-0566-07
作者:
张延苏12吴滢跃13
1. 中国科学院上海技术物理研究所,上海 200083;2. 中国科学院大学,北京 100049;
3. 中国科学院红外探测与成像技术重点实验室,上海 200083
Author(s):
ZHANG Yansu12WU Yingyue13
1. Shanghai Institute of Technical Physics, Shanghai 200083, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China;
3. Key Laboratory of Infrared System Detection and Imaging Technology, Chinese Academy of Sciences, Shanghai 200083, China
关键词:
弱小目标检测FPGAFAST自适应阈值
Keywords:
dim and small target detection FPGA FAST adaptive threshold
分类号:
TP391.41
DOI:
doi:10.11846/j.issn.1001_8891.202006009
文献标志码:
A
摘要:
传统的红外弱小目标检测算法一般采用DSP(digital signal processing)处理器实现,算法复杂且实时性差,本文提出了一种基于FPGA(field programmable gate array)的自适应阈值的FAST(features from accelerated segment test)算法对红外弱小目标进行检测,利用FPGA并行处理的特点,采用流水线设计实现了算法的硬件加速。改进的自适应阈值方法可以根据不同的环境生成合适的阈值,避免了由于阈值选择不当造成的红外弱小目标的丢失或冗余。最后采用4组不同的实测红外图像进行实验,结果表明:该算法能实时地检测出红外图像中的弱小目标,并且能够取得较高的检测率和较低的虚警率,满足实时性和有效性的要求。
Abstract:
The traditional infrared dim and small target detection algorithm is generally implemented by digital signal processing, which is complex and has poor real-time performance. In this study, a features from accelerated segment test (FAST) adaptive-threshold algorithm based on a field programmable gate array (FPGA) is proposed to detect infrared dim and small targets. Based on the characteristics of FPGA parallel processing, the hardware acceleration of the algorithm was realized by a pipeline design. The improved adaptive threshold method can generate appropriate thresholds according to different environments and avoid the loss or redundancy of dim and small infrared targets that is caused by improper threshold selection. Finally, two different groups of infrared images were used for an experiment. The results show that the algorithm can detect dim and small targets in an infrared image in real time and can achieve a high detection rate and low false alarm rate, thereby meeting the requirements of real-time performance and effectiveness.

参考文献/References:

[1] 汪国有, 陈振学, 李乔亮. 复杂背景下红外弱小目标检测的算法研究综述[J]. 红外技术, 2006, 28(5): 287-292.
WANG Gouyou, CHEN Zhenxue, LI Qiaoliang. A review of infrared Weak and Small Targets Detection under Complicated Background[J]. Infrared Technology, 2006, 28(5): 287-292.
[2] 刘杰, 安博文. 海面红外小目标检测算法研究[J]. 红外技术, 2015, 37(1): 16-19.
LIU Jie, AN Bowen. Research on the detection algorithm for infrared small target on the sea[J]. Infrared Technology, 2015, 37(1): 16-19.
[3] 李胜勇, 姜涛, 朱强华. 红外序列图像中小目标实时检测系统设计与实现[J]. 红外技术, 2010, 32(8): 471-474.
LI Shengyong, JIANG Tao, ZHU Qianghua. Design and implement a real-time system for small target detection in infrared image sequence[J]. Infrared Technology, 2010, 32(8): 471-474.
[4] 牟新刚, 张桂林, 丁全心, 等. 基于DSP+FPGA的红外多目标检测系统设计[J]. 红外与激光工程, 2007, 36(S2): 173-176.
MOU Xingang, ZHANG Guilin, DING Quanxin, et al. Design of infrared multi-target detection system based on DSP+FPGA[J]. Infrared and Laser Engineering, 2007, 36(S2): 173-176.
[5] 康令州, 陈福深, 黄自力, 等. 基于DSP+FPGA的红外图像小目标检测系统设计[J]. 电子设计工程, 2010, 18(12): 117-119.
KANG Lingzhou, CHEN Fushen, HUANG Zili, et al. Design of small target detection system in infrared image based on DSP and FPGA[J]. Electronic Design Engineering, 2010, 18(12): 117-119.
[6] 徐文晴, 王敏. 基于自适应形态学滤波的红外小目标检测算法[J]. 激光与红外, 2017(1): 108-113.
XU Wenqing, WANG Min. Infrared small target detection algorithm based on adaptive morphology filter[J]. Laser & Infrared, 2017(1): 108-113.
[7] 张祥越, 丁庆海, 罗海波, 等. 基于改进LCM的红外小目标检测算法[J]. 红外与激光工程, 2017, 46(7): 270-276.
ZHANG Xiangyue, DING Qinghai, LUO Haibo, et al. Infrared dim target detection algorithm based on improved LCM[J]. Infrared & Laser Engineering, 2017, 46(7): 270-276.
[8] BAI X, ZHOU F. Analysis of new top-hat transformation and the application for infrared dim small target detection[J]. Pattern Recognition, 2010, 43(6): 2145-2156.
[9] 刘源, 李庆, 梁艳菊. 基于FPGA的红外目标自动检测系统[J]. 红外技术, 2019, 41(6): 521-526.
LIU Yuan, LI Qing, LIANG Yanju. Implementation of infrared target detection system based on FPGA[J]. Infrared Technology, 2019, 41(6): 521-526.
[10] 杨鲁新, 董文博. 高帧频视觉实时目标检测系统[J]. 电子技术应用, 2019, 45(4): 116-119,124.
YANG Luxin, DONG Wenbo. High-frame-rate visual real-time target detection system[J]. Application of Electronic Technique, 2019, 45(4): 116-119,124.
[11] Rosten E, Drummond T. Machine learning for high-speed corner detection[C]//European Conference on Computer Vision, 2006: 430-443.
[12] 刘亮, 王平, 孙亮. 基于区域灰度变化的自适应FAST角点检测算法[J]. 微电子学与计算机, 2017, 34(3): 20-24.
LIU Liang, WANG Ping, SUN Liang. Adaptive FAST corner detection algorithm based on regional grayscale change[J]. Microelectronics & Computer, 2017, 34(3): 20-24.
[13] 程彪, 黄鲁. 自适应阈值FAST特征点检测算法的FPGA实现[J]. 信息技术与网络安全, 2018, 37(10): 86-90.
CHEN Biao, HUANG Lu. Hardware implementation of adaptive threshold FAST feature point detection algorithm based on FPGA[J]. Information Technology and Network Security, 2018, 37(10): 86-90.
[14] Rosten E, Porter R, Drummond T. Faster and better: a machine learning approach to corner detection[J]. IEEE Trans Pattern Anal Mach Intell., 2008, 32(1): 105-119.
[15] Rublee E, Rabaud V, Konolige K, et al. ORB: An efficient alternative to SIFT or SURF[C]//2011 IEEE International Conference on Computer Vision, Barcelona, 2011: 2548-2555.
[16] 吴金津, 王鹏程, 龙永新, 等. 基于FAST角点检测的图像配准算法[J]. 湖南工业大学学报, 2014, 28(4): 71-75.
WU Jinjin, WANG Pengcheng, LONG Yongxin, et al. Image registration algorithm based on fast corner detection[J]. Journal of Hunan University of Technology, 2014, 28(4): 71-75.

相似文献/References:

[1]秦金明,陈宝国,李丽娟,等. 4×128双色线列红外探测器成像电路设计[J].红外技术,2013,35(02):078.
 QIN Jin-ming,CHEN Bao-guo,LI Li-juan,et al. Imaging Circuit Design of 4×128 Two-color Linear Array Infrared Detector[J].Infrared Technology,2013,35(6):078.
[2]张桥舟,顾国华,陈钱,等.基于两点参数及自适应窗口的实时盲元检测和补偿技术[J].红外技术,2013,35(03):139.
 ZHANG Qiao-zhou,GU Guo-hua,CHEN Qian,et al.Real-time Blind-pixel Detection and Compensation Technology Based on Two-point Parameters and Self-adaptive Window[J].Infrared Technology,2013,35(6):139.
[3]陈明杰,顾国华,陈钱,等.基于FPGA的多通道面阵CCD拼接成像系统[J].红外技术,2013,35(03):161.
 CHEN Ming-jie,GU Guo-hua,CHEN Qian,et al. A Multi-channel CCD Data Processing and Transmission System Based on FPGA[J].Infrared Technology,2013,35(6):161.
[4]路建方,王新赛,肖志洋,等. 基于灰度分层的FPGA红外图像伪彩色实时化研究[J].红外技术,2013,35(05):285.
 LU Jian-fang,WANG Xin-sai,XIAO Zhi-yang,et al. The Research on Real-time Pseudo-color of Infrared Image in FPGA Based on Gray Delaminating[J].Infrared Technology,2013,35(6):285.
[5]樊晓清,顾国华,刘 宁,等.一种红外数字图像伪彩色显示设计[J].红外技术,2013,35(07):398.[doi:10.11846/j.issn.1001_8891.201307003]
 FAN Xiao-qing,GU Guo-hua,LIU Ning,et al.The Design of Pseudo-color Coding and Display For Infrared Digital Images[J].Infrared Technology,2013,35(6):398.[doi:10.11846/j.issn.1001_8891.201307003]
[6]王厚,顾国华,徐富元,等.高速红外视频处理系统的设计研究[J].红外技术,2013,35(07):404.[doi:10.11846/j.issn.1001_8891.201307004]
 WANG Hou,GU Guo-hua,QIAN Wei-xian,et al.Design Research of High-speed Infrared Video Processing System[J].Infrared Technology,2013,35(6):404.[doi:10.11846/j.issn.1001_8891.201307004]
[7]唐耀飞,李杰.基于模板相关匹配的红外目标跟踪FPGA算法实现[J].红外技术,2012,34(03):173.
 TANG Yao-fei,LI Jie.The Implementation of FPGA Based?on Template-matching Infrared Target Tracking Algorithm[J].Infrared Technology,2012,34(6):173.
[8]刘世超,秦洁心,亓洪兴,等.基于SD卡的无人机红外行扫描仪图像采集系统设计[J].红外技术,2012,34(01):053.
 LIU Shi-chao,QIN Jie-xin,QI Hong-xing,et al.Image Acquisition Based on SD Card of UAV IR Line Scanner[J].Infrared Technology,2012,34(6):053.
[9]桂训林,张林,季旭东,等.基于Fusion FPGA的昼夜视频采集处理系统研究[J].红外技术,2011,33(12):707.
 GUI Xun-lin,ZHANG Lin,JI Xu-dong,et al.The Design of Round-the-clock Video Acquisition and Processing SystemBased on Fusion FPGA[J].Infrared Technology,2011,33(6):707.
[10]杨陈晨,顾国华,钱惟贤,等.基于Harris角点的KLT跟踪红外图像配准的硬件实现[J].红外技术,2013,35(10):632.[doi:10.11846/j.issn.1001_8891.201310007]
 YANG Chen-chen,GU Guo-hua,QIAN Wei-xian,et al.Hardware Implementation of Infrared Image Registration Based on the Harris Corner of KLT Tracking [J].Infrared Technology,2013,35(6):632.[doi:10.11846/j.issn.1001_8891.201310007]

备注/Memo

备注/Memo:
收稿日期:2019-12-17;修订日期:2020-04-25.
作者简介:张延苏(1993-),女,河北人,硕士研究生,主要方向:图像处理和目标检测。E-mail:issuyanzhang@163.com。
通信作者:吴滢跃(1980-),男,浙江人,博士(副研究员),主要方向:信号处理、红外成像、目标检测、伺服控制、光电对抗。E-mail:wyyhit@163.com。
更新日期/Last Update: 2020-06-22