Aiming at the problem that there is a hole in the original depth image of Kinect camera, a deep image hole repairing algorithm combining local edge information of color image is proposed. Firs- tly, the smaller holes are repaired by bilateral filtering. Secondly, according to the local edge information of the color image, the larger holes are divided into two types: edgeless and edged. Finally, the average type fill-in repairing is performed on the first type of edgeless holes, and the second type of
ed- ged holes are segmented based on the local edge features of the color image and then gradually repaired from the outside to the end, so as to complete all hole repairing. After the hole repairing is completed, the fusion depth is fused to re-establish the linear spectral clustering kernel function. Based on this, a linear spectral clustering superpixel segmentation algorithm  (LSC-D) is proposed. The experimental results show that, compared with other methods, the proposed deep image hole repairing algorithm  has higher repairing accuracy, and the proposed superpixel segmentation algorithm  has lower under-segmentation error rate and higher boundary recall rate.