关键词: 湿地分类, 特征选择, 多分类器组合

Abstract: Taking features of wetland’s remote sensing image into account, typical feature selection is discussed. The independent component, texture, lake clarity, NDWI, GVI and WI of wetland image are extracted. The classifiers of minimum Euclidean distance, spectral angle mapper, Bayes and supporting vector machine are trained by sample respectively. Weights of every classifier are given by confusion matrices, and whether the sample meets normal distribution is tested. Multi-classifiers combination based on decision network is generated by weights and hypothesis test?result. The experimental results show presented method has better performance and higher accuracy than traditional single-classifier method.

Key words: wetland classification, feature selection, multi-classifiers combination