协同训练支持向量机对遥感影像的分类研究

协同训练可以提高半监督分类器的分类精度，而如何构建具有冗余特性的训练集是其关键所在。依据遥感影像的纹理特征，提出了基于纹理特征值及像素灰度值构建的两个训练集上协同训练支持向量机的算法CTSVMTRS。仿真实验比较了在不同训练集上CTSVMTRS的分类效果，在叠代训练过程中，两类数据集的所有过程的测试结果都存在的明显差异验证了提出的观念。

Research Tri-training SVMS for remote sensing image classification

Tri-training applied in semi-supervised learning can improve the classification precision，but，how to construct two redundance data sets is the key for Tri-training.With the analysing on texture property of remote sensor image，the algorithm CTSVMTRS for Tri-training SVMS in remote sensing image based on two data sets that one is from pixel value and another is from calculating texture property is presented.In the experiment，the keeping distinction of tested result from different Tri-training SVMS generated from two kinds of data sets in each cycle proves the algorithm is effective.