Through SVM algorithm, solving the building problem of input sample featurevector (weak information sample) in the process of extracting mineralizing information from RS data.
解决了应用SVM识别算法对遥感矿化信息提取过程中输入样本特征向量(微弱信息样本)的构造问题。
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According to the method, the energy of different frequency bands after wavelet packet decomposition constitutes the input vectors of support vector machine as feature vectors.
Optimization of feature selection, we select area, perimeter, long axis, short axis, Euler number, geometric moments, and a total of 12 feature parameters as inputvector.