Digital Image Stabilization Based on SURF

In order to stabilize the video images quickly and accurately,the digital image stabilization technology based on speed-up robust features is proposed.Firstly,under the actual requirements and the image sizes to select the queen pattern or local entropy values as the pre-selection operation,which can reduce the time of building feature descriptors.Secondly,using the distance ratio of the vector inner product from the closest neighbor to the second-closest neighbor,to determine the coarse match set,and then removing the mismatches by the cascade feature filters.Finally,both the iterative least squares method and affine model are used to solve the optimal global motion parameters and compensate the current image,and then obtain stable video images.The simulation results show that the effectiveness of the stabilization algorithm,and the computation time is greatly improved compared to the traditional SURF algorithm.