Image stabilization with support vector machine

We propose an image stabilization method based on support vector machine (SVM). Since SVM is very effective in solving nonlinear regression problems, an SVM model was constructed and trained to simulate the vibration characteristic. Then this model was used to predict and compensate for the vibration. A simulation system was built and four assessment metrics including the signal-to-noise ratio (SNR), gray mean gradient (GMG), Laplacian (LAP), and modulation transfer function (MTF) were used to verify our approach. Experimental results showed that this new method allows the image plane to locate stably on the CCD, and high quality images can be obtained.