Fusion processing algorithm of single-photon detection for three-dimensional point cloud and visible light image
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摘要: 为了提升光电系统对于目标的探测识别能力，实现单光子探测三维点云数据和二维可见光图像的融合处理，提出了单光子探测成像系统的融合处理算法，采用直接线性变换方法并利用同名特征点的选取和间接平差算法解决了融合处理过程中的参数标定问题。通过实验数据进行融合处理算法验证，实现了分辨率1024×768像素单光子探测三维点云和二维可见光图像的像素级融合处理。实验结果表明，提出的融合处理算法能够有效实现三维、二维图像的融合。Abstract: In order to improve the detection and identification ability of the photoelectric system for the target, and achieve the fusion processing of single-photon detection of 3D point cloud data and 2D visible light images, the fusion processing algorithm of single-photon detection imaging system was proposed. A direct linear transformation method was used, and the parameter calibration problems in the process of fusion processing were solved by selection of homonymic feature points and indirect adjustment algorithm. The fusion processing algorithm was verified by the experimental data, and the pixel-level fusion processing with 1 024×768 resolution single-photon detection of 3D point cloud data and 2D visible light images was achieved. The experimental results show that the proposed fusion processing algorithm can effectively achieve the fusion of 3D and 2D images.
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Keywords:
- single photon /
- three-dimensional point cloud /
- fusion /
- visible light images
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图 1 单光子探测三维点云数据与可见光相机图像融合处理流程
Figure 1. Fusion processing of single-photon detection for 3D point cloud data and visible camera image
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图 6 融合处理后叠加灰度信息的三维数据
Figure 6. Three dimensional data with gray information after fusion processing
表 1 选取的同名特征点坐标
Table 1 Coordinates of selected homonymous feature points
同名特征
点编号单光子探测三维点
云数据坐标可见光二维图像
数据坐标X Y Z x y 1 −29.818 18.508 202.967 755 111 2 −29.382 13.623 203.706 758 187 3 18.310 9.292 210.774 3 289 4 −0.155 24.807 219.113 280 52 5 4.070 19.222 210.738 212 123 6 −13.211 24.477 216.124 481 53 7 −41.711 −19.570 203.035 973 696 8 18.071 −13.967 215.761 28 647 9 18.814 −11.266 215.044 23 600 
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表 2 融合处理的直接线性变换参数解算结果
Table 2 Calculated results of direct linear transformation parameters by fusion processing
特征参数 解算后的参数值 ${l_1}$ 2.9811 ${l_2}$ 0.3552 ${l_3}$ 1.2046 ${l_4}$ −315.0276 ${l_5}$ −0.5305 ${l_6}$ −2.9367 ${l_7}$ 2.9885 ${l_8}$ −701.5553 ${l_9}$ 0.0009 ${l_{10}}$ −0.0004 ${l_{11}}$ −0.0038
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