Unsupervised retraining of a maximum likelihood classifier for the analysis of multitemporal remote sensing images 论文

详细信息

发表期刊/会议

IEEE Transactions on Geoscience and Remote Sensing

发表日期

2001-01-01

发表年份

2001

摘要

An unsupervised retraining technique for a maximum likelihood (ML) classifier is presented. The proposed technique allows the classifier's parameters, obtained by supervised learning on a specific image, to be updated in a totally unsupervised way on the basis of the distribution of a new image to be classified. This enables the classifier to provide a high accuracy for the new image even when the corresponding training set is not available.