Classification for Remote Sensing Data with Decision Level Fusion

With the development of remote sensing technology,dealing with high-dimension features with traditional classification methods is difficult.Multiple classifiers fusion technology not only deals with high-dimension features but also improves the classification accuracies.We focuses on classifier fusion in decision level,and proposes a new classification method for remote sensing data based on Adaboost.Experiments show that this method is more effective than traditional classification algorithms.