To solve the problem of low resolution of three-dimensional range profile of lidar, a low cost and effective image processing method was used to obtain high resolution three-dimensional range profile. Firstly, according to the characteristics of multi-sensor system, low-resolution Gm-APD lidar and high-resolution ICCD lidar were combined to obtain low-resolution range profile and high-resolution intensity image after registration. Then, an improved image guidance algorithm was proposed to realize super-resolution reconstruction of low-resolution image. Markov random field model was used to define the global energy function, which combined the distance fidelity term with regularization term, and high resolution three-dimensional range profile was obtained by solving the optimization model. By super-resolution reconstruction of simulated image and lidar range profile, the method was validated by objective evaluation indexes of subjective visual effect and image quality. The experimental results show that the method improves the resolution of range profile and protects the edge structure of the image well. It achieves better results than bicubic interpolation, guided filtering and TGV in the evaluation index of no-reference image quality.