loading page

Research on Super-resolution Reconstruction Method of Lidar 3D Range Profile
  • +3
  • Jianfeng Sun,
  • Di Liu,
  • Daoran Gong,
  • Le Ma,
  • Xin Zhang,
  • Penghui Li
Jianfeng Sun
Harbin Institute of Technology
Author Profile
Di Liu
Harbin Institute of Technology
Author Profile
Daoran Gong
Harbin Institute of Technology
Author Profile
Le Ma
Harbin Institute of Technology
Author Profile
Xin Zhang
Harbin Institute of Technology
Author Profile
Penghui Li
Harbin Institute of Technology
Author Profile

Abstract

At present, how to use low-cost and superior algorithms to obtain high-resolution 3D range image is the focus of lidar research. In this letter, the low-resolution Gm-APD lidar is combined with the high-resolution ICCD lidar to obtain the registered low-resolution range image and high-resolution intensity image. This letter proposes an improved image guidance algorithm. The algorithm uses a Markov random field model to define a global energy function. This function combines the distance fidelity term and the regularization term to obtain a high-resolution 3D range image by solving the optimization model. The experimental results show that compared with the traditional algorithms, the algorithm improves the resolution of the range images, the edge of the reconstructed image is sharper than the regional similarity guidance algorithm, and the image quality evaluation index has the better value.