光学 精密工程, 2015, 23 (8): 2328, 网络出版: 2015-10-22   

基于空时域融合处理检测超大视场红外目标

Detection of super wide-field infrared target based on spatial-temporal fusion processing
作者单位
1 军械工程学院 电子与光学工程系, 河北 石家庄 050003
2 中国人民解放军63861部队, 吉林 白城 137001
摘要
针对超大视场红外凝视成像系统用于目标检测时存在的背景复杂、杂波干扰多、目标信息少等问题, 提出了基于空时域融合处理的目标检测方法。该方法在空域部分优化设计Robinson算子, 完成单帧图像的目标初始检测; 然后结合超大视场成像特性, 利用基于天地线检测的图像区域自动划分和空域虚警抑制方法, 有效滤除非目标检测区中的疑似目标。在时域部分则兼顾目标时域特征, 采用基于时域多特征约束的邻域判决法对真实目标进行时域确认。开展了月空背景下的空中目标检测试验, 验证了本文算法的有效性。试验表明: 经空域部分处理后, 原始图像中的背景杂波干扰大大减少, 目标局部信噪比提高了1.3倍以上, 而且疑似目标数目减少了70%; 经时域部分处理后, 可成功检测出红外弱小目标, 并输出其轨迹, 检测概率在95%以上, 而虚警率不足1.5%, 最低目标检测信噪比为2.86。实验表明: 本文方法适用于超大视场图像的红外弱小目标检测, 对地物背景、恒亮孤立点源、瞬时强噪声等干扰有较强的抑制能力, 对点状运动目标有良好的检测效能。
Abstract
When a super wide-field infrared staring system is used to detect a target, it may show complex background, more noise jamming and little target information. Therefore, this paper proposes a spatial-temporal fusion algorithm. In spatial processing, the single image was filtered by an improved Robinson operator, and the primary detection of the target was carried out. Then, the image auto-partition and spatial false-alarm suppression were presented to eliminate the suspected target from a non-target detection region. In temporal processing, the temporal characteristics of the target was considered, the neighbor judgment method was improved to confirm the real target. A detection experiment for the space target was carried out in a moon light, and this proposed algorithm was vilified. It shows that the background interference of original image is suppressed greatly, the local Signal to Noise Ratio(SNR) can be improved more than 1.3 times, the false target number decreases by 70% after spatial processing. Moreover, the infrared weak target is detected successfully with the detection probability of higher than 95%, the false-alarm probability of less than 1.5% and the minimum detection SNR of 2.86 after spatial processing. It concludes that this algorithm is suitable for the infrared weak target detection of super wide-field image and can detect the moving point targets effectively.It has a good suppression effect for background interference, isolated point sources and instantaneous noise.
参考文献

[1] WANG Y Z. Biomimetic staring infrared imaging omnidirectional detection technology[J]. Chinese Science Bulletin, 2010, 55(27-18): 3073-3080.

[2] 王永仲. 鱼眼镜头光学[M]. 北京: 科学出版社, 2006.

    WANG Y ZH. Fisheye Lens Optics[M]. Beijing: Science Press, 2006. (in Chinese)

[3] CHRISTOPHER R B, MARK A M, THOMAS J B. Operational testing and applications of the AIRS FPA with infrared fisheye optics[J]. SPIE, 2003, 4820: 515-524.

[4] BAXTER C R, MASSIE M A, MCCARLEY P L, et al.. MIRIADS-miniature infrared imaging applications development system description and operation [J]. SPIE, 2001, 4369: 129-139.

[5] 李小磊. 法国“阵风”战斗机将装备新一代导弹探测器[EB/OL]. (2010-04-08) http: //www.mod.gov.cn/wqzb/2010-04/08/content_4138532.htm.

    LI X L. The French rafale will be equipped with a new generation of missile detector[EB/OL]. (2010-04-08) http: //www.mod.gov.cn/wqzb/2010-04/08/content_4138532.htm. (in Chinese)

[6] 靳永亮, 王延杰, 刘艳滢, 等. 红外弱小目标的分割预检测[J]. 光学 精密工程, 2012, 20(1): 171-178.

    JIN Y L, WANG Y J, LIU Y Y, et al.. Pre-detection method for small infrared target[J]. Opt. Precision Eng., 2012, 20(1): 171-178. (in Chinese)

[7] 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)

[8] 侯旺, 于起峰, 雷志辉, 等. 基于分块速度域改进迭代运动目标检测算法的红外弱小目标检测[J]. 物理学报, 2014, 63(7): 074208.

    HOU W, YU Q F, LEI ZH H, et al.. A block-based improved recursive moving-target-indication algorithm[J]. Acta Phys. Sin. 2014, 63(7): 074208. (in Chinese)

[9] 王玲玲, 辛云宏. 基于形态学与遗传粒子滤波器的红外小目标检测与跟踪算法[J]. 光子学报, 2013, 42(7): 849-856.

    WANG L L, XIN Y H. A small IR target detection and tracking algorithm based on morphological and genetic particle filter[J]. Acta Photonica Sinica, 2013, 42(7): 849-856. (in Chinese)

[10] WANG K W, XU L J, SUN H Y, et al.. Small target detection and tracking based on hole filling algorithm and Kalman filter [C]. IEEE, 2012 2nd International Conference on Computer Science and Network Technology, Changchun, P.R. China, 2012, 10: 1245-1248.

[11] 穆治亚, 魏仲慧, 何昕, 等. 采用稀疏表示的红外图像自适应杂波抑制[J]. 光学 精密工程, 2013, 21(7): 1850-1857.

    MU ZH Y, WEI ZH H, HE X, et al.. Adaptive clutter suppression of infrared images by using sparse representation [J]. Opt. Precision Eng., 2013, 21(7): 1850-1857. (in Chinese)

[12] 卓宁, 孙华燕, 张海江. 红外图像中弱小目标检测算法概述[J]. 光学仪器, 2005, 27(4): 83-86.

    ZHUO N, SUN H Y, ZHANG H J. Algorithm surveys on small target detection in infrared image[J]. Optical Instruments, 2005, 27(4): 83-86. (in Chinese)

[13] SONG S J, QIN Q. A new algorithm for small target detection in liquid image sequence[C]. IEEE International Conference on Intelligent Control and Information Processing, Dalian, P.R. China, 2011, 5: 234-237.

[14] 柯泽贤, 江汉红, 张朝亮. 时空域结合的红外弱小运动目标检测新方法[J]. 仪器仪表学报, 2013, 34(6): 1401-1405.

    KE Z X, JIANG H H, ZHANG CH L. Novel detection method for small and dim moving infrared target based on spatial-temporal information[J]. Chinese Journal of Scientific Instrument, 2013, 34(6): 1401-1405. (in Chinese)

[15] 王鑫. 复杂背景下红外目标检测与跟踪算法研究[D]. 南京: 南京理工大学, 2010.

    WANG X. Research on infrared target detection and tracking algorithms under complex background[D]. Nanjing: Nanjing University of Science and Technology, 2010. (in Chinese)

[16] 管志强, 陈钱, 钱惟贤, 等. 一种背景自适应调整的弱点目标探测算法[J]. 光学学报, 2007, 27(12): 2163-2168.

    GUAN ZH Q, CHEN Q, QIAN W X, et al.. An adaptive background adjusting algorithm for dim target detection[J]. Acta Optica Sinica, 2007, 27(12): 2163-2168. (in Chinese)

[17] XU F Y, GU G H, QIAN W X. The research and implementation of CFAR in infrared small target detection[C]. International Symposium on Photoelectronic Detection and Imaging 2011: Advances in infrared Imaging and Applications, Beijing, P.R. China, 2011, 8193: 1N1-1N10.

[18] 鲁居强, 王新增, 刘顺生, 等. 基于八邻域判决的红外运动小目标检测方法[J]. 红外, 2006, 27(9): 20-23.

    LU J Q, WANG X Z, LIU SH SH, et al.. A method for detecting small infrared moving target based on eight close area judgement[J]. Infrared, 2006, 27(9): 20-23. (in Chinese)

黄富瑜, 沈学举, 刘旭敏, 崔铁成. 基于空时域融合处理检测超大视场红外目标[J]. 光学 精密工程, 2015, 23(8): 2328. HUANG Fu-yu, SHEN Xue-ju, LIU Xu-min, CUI Tie-cheng. Detection of super wide-field infrared target based on spatial-temporal fusion processing[J]. Optics and Precision Engineering, 2015, 23(8): 2328.

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