Smooth implementation of this project, for solving uncertain information in remote sensing image classification has a high theoretical value and a good prospect.
本项目的顺利开展，对于解决遥感影像中不确定信息分类问题具有较高的理论价值和良好的应用前景。
Current remote sensing image classification models and algorithms commonly used statistical methods, neural networks, Bayesian and so on.
目前遥感影像分类的常用模型和算法有统计学方法、神经网络、贝叶斯等。
Then, an experiment of remote sensing image classification is carried out to verify the authenticity based on the relations between samples and bands.
然后，在遥感影像分类实验中，借助样本数量与波段数目的关系，验证了理论分析的结果。
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