Based on idiotypic immune network theory, a Regional-memory-pattern Artificial idiotypic network (RAIN) is proposed to classify multi-spectral remote sensing image.
摘要基于独特型免疫网络原理，提出了一种新型的分区记忆模式人工独特型网络模型，并利用其对卫星遥感数据进行了分类。
Thus, some scholars use object-oriented information extraction technology to classify the remote sensing image, greatly increased the accuracy of high-resolution remote sensing image classification.
于是，有些学者将面向对象信息提取技术运用到遥感影像的分类中，大大提高了高分辨率遥感影像的分类精度。
Finally, the three SVM classifier kernel functions are used to classify BSQ remote sensing image in TM6 band, the experimental data shows their feasibility and higher efficiency.
最后通过对TM 6波段bs Q格式遥感图像进行分类对比证明了SVM分类器核函数用于TM图像分类的可行性及高效性。
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