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Image stabilization with support vector machine

机译:支持向量机的图像稳定

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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.
机译:我们提出了一种基于支持向量机(SVM)的图像稳定方法。由于SVM在解决非线性回归问题方面非常有效,因此构建并训练了SVM模型以模拟振动特性。然后,使用该模型预测和补偿振动。建立了一个仿真系统,并使用四个评估指标(包括信噪比(SNR),灰度平均梯度(GMG),拉普拉斯算子(LAP)和调制传递函数(MTF))来验证我们的方法。实验结果表明,该新方法可以使图像平面稳定地定位在CCD上,可以获得高质量的图像。

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