面向对象遥感影像分类中的样本选择与基于像素的方法有很大不同，基于统计学理论，研究了面向对象方法的样本数量选择问题。首先，针对面向对象方法的特点，对影像特征空间进行分析，结果表明面向对象方法中要求训练样本的数量可以显著地减少。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。

As opposed to per-pixel classification, the selection of training samples is different in object-oriented method. Based on statistical theory, the number of training samples required in object-oriented classification is studied in this paper. First，feature space analysis of images is implemented in object-oriented classification, which shows that the number of training samples needed for object-oriented classification is much less than that in per-pixel classification. Then, an experiment of remote sensing image classification is carried out to verify the authenticity based on the relations between samples and bands.