留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

中波红外相机盲元的实时动态检测与补偿方法

孙超 张洪文 王沛 李军

孙超, 张洪文, 王沛, 李军. 中波红外相机盲元的实时动态检测与补偿方法[J]. 红外技术, 2021, 43(9): 869-875.
引用本文: 孙超, 张洪文, 王沛, 李军. 中波红外相机盲元的实时动态检测与补偿方法[J]. 红外技术, 2021, 43(9): 869-875.
SUN Chao, ZHANG Hongwen, WANG Pei, LI Jun. Real-time Dynamic Blind Pixel Detection and Compensation Method for Mid-wave Infrared Camera[J]. Infrared Technology , 2021, 43(9): 869-875.
Citation: SUN Chao, ZHANG Hongwen, WANG Pei, LI Jun. Real-time Dynamic Blind Pixel Detection and Compensation Method for Mid-wave Infrared Camera[J]. Infrared Technology , 2021, 43(9): 869-875.

中波红外相机盲元的实时动态检测与补偿方法

详细信息
    作者简介:

    孙超(1986-), 男, 吉林四平人, 助理研究员, 研究方向为航空光学成像与测量技术。E-mail: chaosxjtu@163.com

  • 中图分类号: TN215

Real-time Dynamic Blind Pixel Detection and Compensation Method for Mid-wave Infrared Camera

  • 摘要: 盲元的存在严重影响了红外相机的成像质量,基于场景的盲元检测与补偿方法可以有效地解决此类问题。本文提出了一种改进的局部“3σ”方法,通过计算图像的三维噪声获得图像的平均噪声,据此得到盲元检测的最小判据,然后采用局部“3σ”方法和中值滤波法对盲元进行实时的动态检测与补偿,并将该方法应用于自研的某中波红外相机中。对黑体成像实验的结果表明,本文方法与辐射定标法相比,盲元检出的重合度平均可以达到82%以上;与传统的局部“3σ”方法相比具有相同的盲元检测与补偿效果,但可以将盲元的过检率降低30%以上;地面及载机挂飞成像实验的结果表明,本文方法可以对盲元起到很好地抑制作用,红外相机的昼间和夜间图像均不存在明显异常的黑、白点,图像中景物细节丰富、图像质量优良。因此,本文方法可以对盲元进行实时的动态检测与补偿,在自研的中波红外相机中的运用是可行和有效的。
  • 图  1  红外图像对比(局部)

    Figure  1.  Comparison of infrared images(partial)

    图  2  含有盲元的红外相机航拍图像(局部)

    Figure  2.  Aerial image with blind pixel of infrared camera (partial)

    图  3  红外图像的灰度空间分布

    Figure  3.  Spatial distribution of grayscale in an IR image

    图  4  红外图像对比(局部)

    Figure  4.  Comparison of infrared images (partial)

    图  5  开启盲元补偿功能的地面外景红外图像

    Figure  5.  Infrared image of ground after turning on the blind pixel compensation function

    图  6  昼间红外相机航拍图像

    Figure  6.  Aerial image taken by infrared camera in the daytime

    图  7  夜间红外相机航拍图像

    Figure  7.  Aerial image taken by infrared camera at night

    表  1  辐射定标法和本文方法的对比(20℃黑体成像)

    Table  1.   Comparison of methods of radiation calibration and this paper (imaging blackbody at 20℃)

    Image’s number Method of radiation calibration Method of this paper Coincidence number of blind pixel detection Coincidence percentage of blind pixel detection
    1 4791 8679 4096 85.49%
    2 5856 9742 4880 83.33%
    3 6220 9809 5015 80.63%
    4 6089 10331 5041 82.79%
    5 4940 9502 4208 85.18%
    6 5074 9466 4264 84.04%
    7 6328 9989 5104 80.66%
    8 5768 9569 4726 81.93%
    9 6690 10736 5379 80.40%
    10 5058 9008 4272 84.46%
    On average 5681 9683 4699 82.71%
    下载: 导出CSV

    表  2  局部“3σ”方法和本文方法的对比(20℃黑体成像)

    Table  2.   Comparison of methods of local "3σ" and this paper (imaging blackbody at 20℃)

    Algorithm Method of local “3σ” Method of this paper
    Average noise after blind pixel compensation 5.4016 5.4263
    Number of blind pixel in original image 4378 4311
    Number of residual blind pixel after compensation 135 135
    Average number of blind pixel compensated for 20 images 14205 10091
    下载: 导出CSV

    表  3  局部“3σ”方法和本文方法的对比(5℃黑体成像)

    Table  3.   Comparison of methods of local "3σ" and this paper(imaging blackbody at 5℃)

    Algorithm Method of
    local “3σ”
    Method of
    this paper
    Average noise after blind pixel compensation 5.0913 5.1050
    Number of blind pixel in original image 2179 2155
    Number of residual blind pixel after compensation 36 34
    Average number of blind pixel compensated for 20 images 13142 9814
    下载: 导出CSV
  • [1] 沈宏海, 黄猛, 李嘉全, 等. 国外先进航空光电载荷的进展与关键技术分析[J]. 中国光学, 2012, 5(1): 20-29. doi:  10.3969/j.issn.2095-1531.2012.01.003

    SHEN Honghai, HUANG Meng, LI Jiaquan, et al. Recent progress in aerial electro - optic payloads and their key technologies[J]. Chinese Optics, 2012, 5(1): 20-29. doi:  10.3969/j.issn.2095-1531.2012.01.003
    [2] 王岳, 李双喜, 王磊. 红外航空相机技术研究[J]. 激光与红外, 2017, 47(12): 1468-1472. doi:  10.3969/j.issn.1001-5078.2017.12.003

    WANG Yue, LI Shuangxi, WANG Lei. Study on infrared aerial camera technology[J]. Laser & Infrared, 2017, 47(12): 1468-1472. doi:  10.3969/j.issn.1001-5078.2017.12.003
    [3] 李凌霄, 冯华君, 赵巨峰, 等. 红外焦平面阵列的盲元自适应快速校正[J]. 光学精密工程, 2017, 25(4): 477-486. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201704024.htm

    LI Lingxiao, FENG Huajun, ZHAO Jufeng, et al. Adaptive and fast blind pixel correction of IRFPA[J]. Optics and Precision Engineering, 2017, 25(4): 477-486. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201704024.htm
    [4] GHOSH S, MARSHALL I, FREITAS A. Autonomously detecting the defective pixels in an imaging sensor array using a robust statistical technique[C]//Proc. SPIE, Image Quality and System Performance V, San Jose, CA, 2008, 6808: 680813-1-680813-12.
    [5] 刘高睿, 孙胜利, 林长青, 等. 红外线列探测器闪元噪声分析与抑制方法[J]. 红外与毫米波学报, 2018, 37(4): 421-426. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYH201804008.htm

    LIU Gaorui, SUN Shengli, LIN Changqing, et al. Analysis and suppression method of flickering pixel noise in images of infrared linear detector[J]. J. Infrared Millim. Waves, 2018, 37(4): 421-426. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYH201804008.htm
    [6] 张长兴, 刘成玉, 丌洪兴, 等. 热红外高光谱成像仪光谱匹配盲元检测算法[J]. 红外与激光工程, 2020, 49(1): 0104002-1-0104002-7. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYJ202001014.htm

    ZHANG Changxing, LIU Chengyu, QI Hongxing, et al. Blind pixel detection algorithm using spectral matching for thermal infared hyperspectral imager[J]. Infrared and Laser Engineering, 2020, 49(1): 0104002-1-0104002-7. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYJ202001014.htm
    [7] 周慧鑫, 魏亚姣, 秦翰林, 等. 采用双阈值的非制冷IRFPA盲元迭代检测算法[J]. 红外与激光工程, 2011, 40(5): 795-799. doi:  10.3969/j.issn.1007-2276.2011.05.004

    ZHOU Huixin, WEI Yajiao, QIN Hanlin, et al. Blind-pixel iterative detection algorithm based on double threshold for uncooled IRFPA[J]. Infrared and Laser Engineering, 2011, 40(5): 795-799. doi:  10.3969/j.issn.1007-2276.2011.05.004
    [8] 冷寒冰, 宫振东, 谢庆胜, 等. 基于模糊中值的IRFPA自适应盲元检测与补偿[J]. 红外与激光工程, 2015, 44(3): 821-826. doi:  10.3969/j.issn.1007-2276.2015.03.006

    LENG Hanbing, GONG Zhendong, XIE Qingsheng, et al. Adaptive blind pixel detection and compensation for IRFPA based on fuzzy median filter[J]. Infrared and Laser Engineering, 2015, 44(3): 821-826. doi:  10.3969/j.issn.1007-2276.2015.03.006
    [9] 顾国华. 基于滑动窗口与多帧补偿的自适应盲元检测与补偿算法[J]. 红外技术, 2010, 32(7): 420-423. doi:  10.3969/j.issn.1001-8891.2010.07.013

    GU Guohua. A Blind Pixel Self-adaptive Detection And Compensation Algorithm Based on Sliding Window and Multi-frame Compensation[J]. Infrared Technology, 2010, 32(7): 420-423. doi:  10.3969/j.issn.1001-8891.2010.07.013
    [10] 郑骁, 葛志雄, 赖永安. 基于滑动窗口的红外焦平面阵列盲元检测算法研究[J]. 红外技术, 2019, 41(8): 735-741. http://hwjs.nvir.cn/article/id/hwjs201908008

    ZHENG Xiao, GE Zhixiong, LAI Yong'an. Algorithm for Blind-pixel Detection of IRFPA Based on Sliding Window[J]. Infrared Technology, 2019, 41(8): 735-741. http://hwjs.nvir.cn/article/id/hwjs201908008
    [11] 詹维, 马新星, 徐子剑. 基于超像素分割的红外盲元检测及校正[J]. 红外技术, 2018, 40(11): 1085-1090. http://hwjs.nvir.cn/article/id/hwjs201811012

    ZHAN Wei, MA Xinxing, XU Zijian. IR Blind Pixels Detection and Correction Based on Superpixel Segmentation[J]. Infrared Technology, 2018, 40(11): 1085-1090. http://hwjs.nvir.cn/article/id/hwjs201811012
    [12] 张北伟, 曹江涛, 丛秋梅. 基于曲面拟合的红外图像盲元检测方法[J]. 红外技术, 2017, 39(11): 1007-1011. http://hwjs.nvir.cn/article/id/hwjs201711007

    ZHANG Beiwei, CAO Jiangtao, CONG Qiumei. Detection Method for Infrared-image Blind Pixels Based on Curved-surface Fitting[J]. Infrared Technology, 2017, 39(11): 1007-1011. http://hwjs.nvir.cn/article/id/hwjs201711007
    [13] 粟宇路, 苏兰, 陈大乾, 等. 基于分布搜索策略的自适应盲元检测算法[J]. 红外技术, 2016, 38(6): 457-460. http://hwjs.nvir.cn/article/id/hwjs201606002

    SU Yulu, SU Lan, CHEN Daqian, et al. Adaptive Blind Pixel Detection Algorithms Based on Stepwise Search Strategy[J]. Infrared Technology, 2016, 38(6): 457-460. http://hwjs.nvir.cn/article/id/hwjs201606002
    [14] 国家技术监督局. GB/T 17444-2013. 红外焦平面阵列参数测试方法[S]. 北京: 中国标准出版社, 2014.

    The State Bureau of Quality and Technical Supervision. GB/T 17444-2013. Measuring methods for parameters of infrared focal plane arrays[S]. Beijing: Standards Press of China, 2014.
    [15] John D Agostino, Curtis Webb. Three-dimensional analysis framework and measurement methodology for imaging system noise[C]//Proc. SPIE, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing Ⅱ, 1991, 1488: 110-121.
    [16] Patrick O'Shea, Stephen Sousk. Practical Issues with 3D-Noise Measurements and Application to Modern Infrared Sensors[C]//Proc. SPIE, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVI, 2005, 5784: 262-271.
  • 加载中
图(7) / 表(3)
计量
  • 文章访问数:  28
  • HTML全文浏览量:  15
  • PDF下载量:  16
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-05-12
  • 修回日期:  2021-08-07
  • 刊出日期:  2021-09-20

目录

    /

    返回文章
    返回

    《红外技术》网站维护通知

    尊敬的专家、作者、读者:

    国庆假期期间(10月1日-3日)因设备维护,《红外技术》网站(hwjs.nvir.cn)将于2021年9月30日18:00-10月4日13:00关闭。关闭期间,您将暂时无法访问《红外技术》网站和登录投审稿系统,给您带来不便敬请谅解!

    《红外技术》编辑部

    2021年9月29日