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压缩感知光谱成像技术的编码孔径与探测器匹配优化

刘铭鑫 张新 王灵杰 史广维 吴洪波 付强

刘铭鑫, 张新, 王灵杰, 史广维, 吴洪波, 付强. 压缩感知光谱成像技术的编码孔径与探测器匹配优化[J]. 中国光学, 2020, 13(2): 290-301. doi: 10.3788/CO.20201302.0290
引用本文: 刘铭鑫, 张新, 王灵杰, 史广维, 吴洪波, 付强. 压缩感知光谱成像技术的编码孔径与探测器匹配优化[J]. 中国光学, 2020, 13(2): 290-301. doi: 10.3788/CO.20201302.0290
LIU Ming-xin, ZHANG Xin, WANG Ling-jie, SHI Guang-wei, WU Hong-bo, FU Qiang. Optimization of matching coded aperture with detector based on compressed sensing spectral imaging technology[J]. Chinese Optics, 2020, 13(2): 290-301. doi: 10.3788/CO.20201302.0290
Citation: LIU Ming-xin, ZHANG Xin, WANG Ling-jie, SHI Guang-wei, WU Hong-bo, FU Qiang. Optimization of matching coded aperture with detector based on compressed sensing spectral imaging technology[J]. Chinese Optics, 2020, 13(2): 290-301. doi: 10.3788/CO.20201302.0290

压缩感知光谱成像技术的编码孔径与探测器匹配优化

doi: 10.3788/CO.20201302.0290
基金项目: 

国家自然科学基金 61505201

吉林省科技发展计划青年科研基金 20160520175JH

详细信息
    作者简介:

    刘铭鑫(1991—), 男, 吉林辽源人, 博士研究生, 主要从事计算成像及光学设计方向研究。E-mail:13261531101@163.com

    张新(1968—), 男, 研究员, 博士生导师, 主要从事光学设计, 灵巧光学的光机一体化设计, 计算成像方向研究, E-mail:optlab@ciomp.ac.cn

  • 中图分类号: V248.3

Optimization of matching coded aperture with detector based on compressed sensing spectral imaging technology

Funds: 

National Natural Science Foundation of China 61505201

Youth scientific research found of Jilin provice science and technology decelopment plan 20160520175JH

More Information
  • 摘要: 编码孔径光谱成像仪在实际应用中存在着编码模板与探测器分辨率不匹配从而降低系统分辨率的问题。针对该问题进行了两种情况分析,并通过数学理论建模给出了相应的解决方案。对于编码模板分辨率高于探测器分辨率这一情况,提出引入邻域嵌入超分辨技术的方法,实现了基于压缩感知的超分辨光谱成像。对于编码模板分辨率低于探测器分辨率这一情况,提出区块阈值划分的编码孔径,将编码微元按照区块阈值重新划分并进行灰度分级,从而实现低分辨率编码模板的高分辨率编码孔径。利用梯度投影稀疏重构(GPSR)算法进行数据立方体重建,实验结果表明:运用基于超分辨理论的编码孔径快照光谱成像系统所测得的光谱图像更精准,内容更丰富;采用基于区块阈值划分的编码孔径的编码孔径快照光谱成像系统具有更高的空间分辨率和光谱分辨率。结果证实优化后的编码孔径快照光谱成像系统,其分辨率和成像质量大幅度提升,并实现了高分辨率元件的100%利用。
  • 图  1  编码孔径快照光谱成像系统的结构示意图

    Figure  1.  Structral diagram of coded aperture snapshot spectral imaging system

    图  2  探测器划分原理

    Figure  2.  Detector division principle

    图  3  超分辨光谱成像算法流程

    Figure  3.  Flow chart of super resolution spectral imaging algorithm

    图  4  区块阈值划分过程

    Figure  4.  Block threshold partitioning

    图  5  CASSI桌面实验系统

    Figure  5.  CASSI desktop experiment system

    图  6  3种情况下测量结果对比图

    Figure  6.  Comparison of measurement results in three cases

    图  7  一般的CASSI系统(上)与改进型(下)重建结果对比

    Figure  7.  Comparison results of general CASSI system(up) and improved reconstruction (down)

    图  8  目标场景和地物光谱仪在3个点处的特征曲线

    Figure  8.  Characteristic curves of target scene and ground-object spectrometer at three points

    图  9  一般CASSI系统、超分辨CASSI系统及商用光谱仪的光谱曲线对比

    Figure  9.  Comparison of spectral curves of a general CASSI system, a super-resolution CASSI system and a commercial spectrometer

    图  10  编码模板及其区块阈值划分处理后的示意图

    Figure  10.  Schematic diagram of coding template and its block threshold partitioning

    图  11  一般的CASSI系统(上)与改进型(下)重建结果对比

    Figure  11.  Comparison of reconstruction results of general CASSI system(up) and modified CASSI system(down)

    图  12  一般CASSI系统、区块阈值划分CASSI系统及ASD光谱仪的光谱曲线对比

    Figure  12.  Comparison of spectral curves of a general CASSI system, a block threshold partitioning CASSI system and ASD spectrometer

    表  1  系统参数

    Table  1.   System parameters

    元件 参数
    DMD: 分辨率:1 024×768
    空间光调制器DLP1100 微元尺寸:13.68 μm×13.68 μm
    探测器: 分辨率:656×492
    GuppyPro F-032C 像元尺寸:7.4 μm×7.4 μm
    分光原件 透射式光栅
    光谱范围 450~680 nm
    光谱分辨率 ≤20 nm@540 nm
    系统焦距 75 mm
    系统F 4
    下载: 导出CSV

    表  2  3种实验条件下的测量结果对比

    Table  2.   Comparison of measurement results under three experimental conditions

    像素尺寸(μm) 分辨率(像素)
    Δc Δd 编码孔径 空间分辨率 光谱通道
    一般CASSI 27.36 29.7 160×160 160×160 8
    超分辨CASSI 13.68 29.7 320×320 320×320 8
    区块阈值划分CASSI 13.68 9.9 320×320 480×480 24
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-04-28
  • 修回日期:  2019-05-22
  • 刊出日期:  2020-04-01

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