The field of vision of deep-sea submersibles is usually limited， and it is difficult to comprehensively observe the surrounding seabed through the video image of a single field of vision， which makes it more difficult for researchers to understand the overall distribution of seabed substrate. To solve the above problems， this paper proposes a fast stitching method of seabed substrate image based on the deep-sea submersible image. Firstly， the red channel of the video frame is corrected based on the image enhancement method of channel compensation， and the brightness enhancement and CLAHE processing are carried out. Secondly， the CUDA accelerated SURF algorithm is used to extract feature points and descriptors， and the KD tree algorithm is used to initially match the feature points of the front and back frames. Then， the KNN classification algorithm is used to eliminate the mismatching， and the interframe motion estimation is carried out for the screened matching points. The base map is generated through the transformation matrix and the front and rear frames are spliced. Finally， the feature point coordinates and interframe motion information are fused， and the above process is repeated to generate a continuous mosaic image. The video images obtained by “Jiaolong” in a certain voyage are used for mosaic processing experiments. The results show that this method has a good mosaic effect， and its feasibility is verified.