# Super-Resolution Reconstruction of an Array Lidar Range Profile
## 4 Conclusions  
A POCS super-resolution reconstruction method combining the LK optical flow method and the Gaussian pyramid is proposed in this paper. The method solves the problems of the low resolution of range profiles formed by array lidar and the low retention of target details and edge information by the traditional super-resolution methods.  
We compared the method presented in this paper with bilinear interpolation, bicubic interpolation, POCS, and POCS with adaptive correction thresholding using the dataset and the actual data taken from the laboratory-built GM-APD lidar system.  
The experimental results show that the proposed method outperforms the other methods in terms of the AG and ES under different super-resolution conditions. In the experiments on the redwood-3 dscan dataset, the method proposed in this paper improves the AG by at least 10.12% and the ES by at least 7.02% over the conventional POCS; in the experiments with real mining data, the method proposed in this paper shows at least 9.11% improvement in the AG and at least 9.03% improvement in the ES over the conventional POCS.  
It can be seen that the super-resolved range profile can also clearly display the detailed contours of different targets when the distance between the targets is close, which proves that the proposed method can effectively retain the target details and edge information while improving the resolution of the range profile.  
Conceptualization, X.Z. and C.W.; methodology, X.Z. and C.W.; software, C.S. and X.L.; validation, G.X. and R.Z.; formal analysis, C.S. and X.L.; writing--original draft preparation, X.Z.; writing--review and editing, X.Z. and C.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Key R&D Program of China (Grant No. 2022 YFC3803702) and the Shaanxi Provincial Science and Technology Department's Innovative Talent Promotion Program-Youth Science and Technology Rising Star Project (Grant No. 2023 KJXX-055).  
Not applicable.  
Data Availability Statement: Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.  
The manuscript was supported by the Xi'an Key Laboratory of Active Photoelectric Imaging Detection Technology.  
The authors declare no conflicts of interest.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**AG**} & \multicolumn{2}{c}{**ES**} & \multicolumn{2}{c}{**Time/ms**} \\ \cline{2-10}  & \(\times\)**2** & \(\times\)**4** & \(\times\)**8** & \(\times\)**2** & \(\times\)**4** & \(\times\)**8** & \(\times\)**2** & \(\times\)**4** & \(\times\)**8** \\ \hline Bilinear & 0.22 & 0.12 & 0.06 & 2.35 & 1.35 & 0.68 & 4.4 & 6.1 & 7.8 \\ Bicubic & 0.28 & 0.14 & 0.07 & 2.74 & 1.58 & 0.83 & 5.8 & 7.9 & 8.7 \\ POCS & 7.13 & 4.66 & 3.76 & 69.06 & 44.57 & 29.91 & 17.8 & 24.7 & 33.5 \\ POCS [17] & 7.31 & 4.78 & 3.85 & 74.29 & 47.38 & 31.15 & 24.6 & 30.4 & 36.1 \\ Proposed & 7.59 & 5.03 & 3.98 & 78.84 & 51.11 & 33.08 & 28.3 & 34.1 & 41.3 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Comparison of the evaluation indicators of the outdoor scene range profile under different magnifications.