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.