Improved support vector machine and classification for remotely sensed data
改进的P-SVM支持向量机与遥感数据分类

In this paper, the P-SVM algorithm was introduced into multi-spectral/high-spatial resolution remotely sensed data classification and it is applied to classification of ASTER satellite data and ADS40 aerial digital data. The experiments indicate that the P-SVM is at least competitive with the standard SVM algorithm in classification accuracy of remotely sensed data and the time needed is less.