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基于三色LCTF的自然感彩色微光EBAPS成像系统

刘璇 李瑞强 李力 金伟其 程宏昌 闫磊 郑舟

刘璇, 李瑞强, 李力, 金伟其, 程宏昌, 闫磊, 郑舟. 基于三色LCTF的自然感彩色微光EBAPS成像系统[J]. 应用光学, 2022, 43(6): 1044-1053. doi: 10.5768/JAO202243.0604002
引用本文: 刘璇, 李瑞强, 李力, 金伟其, 程宏昌, 闫磊, 郑舟. 基于三色LCTF的自然感彩色微光EBAPS成像系统[J]. 应用光学, 2022, 43(6): 1044-1053. doi: 10.5768/JAO202243.0604002
LIU Xuan, LI Ruiqiang, LI Li, JIN Weiqi, CHENG Hongchang, YAN Lei, ZHENG Zhou. Natural color low-level-light EBAPS imaging system based on three-color LCTF[J]. Journal of Applied Optics, 2022, 43(6): 1044-1053. doi: 10.5768/JAO202243.0604002
Citation: LIU Xuan, LI Ruiqiang, LI Li, JIN Weiqi, CHENG Hongchang, YAN Lei, ZHENG Zhou. Natural color low-level-light EBAPS imaging system based on three-color LCTF[J]. Journal of Applied Optics, 2022, 43(6): 1044-1053. doi: 10.5768/JAO202243.0604002

基于三色LCTF的自然感彩色微光EBAPS成像系统

doi: 10.5768/JAO202243.0604002
基金项目: 国防基础科研项目(2019-JCJQ-ZD-006-00)
详细信息
    作者简介:

    刘璇(1997—),女,博士研究生,主要从事光电成像理论与技术研究。E-mail:3120205295@bit.edu.cn

    通讯作者:

    李力(1982—),男,副教授,主要从事光电成像与视频处理技术研究。Email:lili@bit.edu.cn

  • 中图分类号: TN206

Natural color low-level-light EBAPS imaging system based on three-color LCTF

  • 摘要: 高灵敏度电子轰击有源像素传感器(electron bombarded active pixel sensor, EBAPS)既有真空成像器件的高增益、高灵敏度特性,又有固体成像器件的数字化特征,极大地提升了夜视成像水平。该文基于三色液晶可调制滤光片(liquid crystal tunable filter, LCTF)搭建了自然感彩色微光EBAPS成像系统,并根据微光图像特性,对系统获得的彩色图像进行了灰度拉伸、白平衡、色彩校正等色彩增强处理。实验结果表明:该系统可实现反映景物本身颜色特点且具有自然感的低照度彩色成像,有效提升夜间对目标景物特点的观察效果,可以在5×10−4 lx照度下实现彩色成像。
  • 图  1  EBAPS成像原理示意图

    Fig.  1  Schematic diagram of EBAPS imaging principle

    图  2  彩色微光EBAPS图像采集实验系统

    Fig.  2  Experimental system of color low-level-light EBAPS image acquisition

    图  3  系统模型

    Fig.  3  Diagram of system model

    图  4  Meadowlark Optics的三色LCTF及其控制器

    Fig.  4  Three-color LCTF and its controller of Meadowlark Optics

    图  5  EBAPS及其系统实物

    Fig.  5  EBAPS and physical integrated system

    图  6  几种典型光电阴极的光谱响应

    Fig.  6  Spectral responses of several typical photocathodes

    图  7  EBAPS成像过曝区域及噪声点

    Fig.  7  Imaging overexposed areas and noise spots of EBAPS

    图  8  实验所用标准色卡

    Fig.  8  Standard color checkers used in experiment

    图  9  色块光谱反射率

    Fig.  9  Spectral reflectance of color blocks

    图  10  2种颜色空间模型与2种回归方法计算彩色校正结果

    Fig.  10  Color correction results calculated by two color space models and two regression methods

    图  11  场景1在不同照度下图像处理效果

    Fig.  11  Image processing effect under different illuminance in scene 1

    图  12  场景2在不同照度下图像处理效果

    Fig.  12  Image processing effect under different illuminance in scene 2

    表  1  回归方法及其计算形式

    Table  1  Regression method and its calculation form

    回归方法色彩校正矩阵TCCM计算形式
    QLSR${{{\boldsymbol{T}}}_{{\text{CCM}}}}{ = }{{\boldsymbol{Q}}}{{{\boldsymbol{P}}}^{\rm{T}}}{({{\boldsymbol{P}}}{{{\boldsymbol{P}}}^{\rm{T}}})^{ - 1}}$
    PLSR${{{\boldsymbol{T}}}_{{\text{CCM}}}}{ = }{{\boldsymbol{Q}}}{{{\boldsymbol{P}}}^{\rm{T}}}{({{\boldsymbol{P}}}{{{\boldsymbol{P}}}^{\rm{T}}} + \lambda {{\boldsymbol{I}}})^{ - 1}}$
    下载: 导出CSV

    表  2  颜色空间模型

    Table  2  Color space model

    颜色空间模型标准矩阵Q测量矩阵P变换形式
    线性模型${{\boldsymbol{Q}}} = \left[ {\begin{array}{*{20}{c}} {{R_{\text{S}}}}&{{G_{\text{S}}}}&{{B_{\text{S}}}} \end{array}} \right]$${{\boldsymbol{P}}} = \left[ {\begin{array}{*{20}{c}} {{R_{\text{M}}}}&{{G_{\text{M}}}}&{{B_{\text{M}}}} \end{array}} \right]$${{{\boldsymbol{Q}}}^{\rm{T}}} = {{{\boldsymbol{T}}}_{{\text{CCM}}}}{{{\boldsymbol{P}}}^{\rm{T}}}$
    复合模型${{\boldsymbol{Q}}} = \left[ {\begin{array}{*{20}{c}} {\ln ({R_{\text{S}}})}&{\ln ({G_{\text{S}}})}&{\ln ({B_{\text{S}}})} \end{array}} \right]$$ {{\boldsymbol{P}}} = \left[ {\begin{array}{*{20}{c}} {{R_{\text{M}}}}&{{G_{\text{M}}}}&{{B_{\text{M}}}}&1 \end{array}} \right] $${{{\boldsymbol{Q}}}^{\rm{T}}} = {{{\boldsymbol{T}}}_{{\text{CCM}}}}{{{\boldsymbol{P}}}^{\rm{T}}}$
    下载: 导出CSV

    表  3  场景1图像评价指标参数

    Table  3  Image evaluation index parameters of scene 1

    图像色差/NBS饱和度
    拉伸后图像白平衡后图像色彩校正图像白平衡后图像色彩校正图像
    (a)31.769129.758416.80680.18441.1775
    (b)31.193730.483318.96070.16351.0684
    (c)36.534529.081518.96070.22151.0684
    (d)30.420736.724320.22950.13311.1416
    (e)31.897641.860322.78040.10001.1341
    (f)34.185444.203625.60880.09471.1602
    (g)39.894248.182729.42660.07181.0503
    (h)49.530553.823527.16700.02850.8663
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-08-17
  • 修回日期:  2022-10-05
  • 刊出日期:  2022-11-14

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