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.