Digital Image Stabilization Based on Improved Scale Invariant Feature Transform

A novel digital image stabilization approach using Harris and Scale Invariant Feature Transform (SIFT) was presented in this article. Using SIFT in digital image stabilization, too many feature points and matches were extracted, but some of them were not so stable. Using these feature points and matches can not only increase the computational effort, but also enhance the wrong matching probability. We proposed to use SIFT to detect feature points and incorporate the Harris criterion to select the most stable feature points in the video sequence where image motion was happened due to vehicle or platform vibration. With these feature points, we use general feature descriptor and matching algorithm to achieve the image stabilization. Experimental results show that the proposed algorithm can not only bring down the probability of wrong matching and get more accurate matches, but also reduce the computation burden than SIFT effectively.