Evaluation of local features for scene classification using VHR satellite images
Lijun Chen, Wen Tao Yang, Kan Xu, Tao Xu · 2011
We compare the scene classification performance of 13 features, including structure, texture and color features. First, image classification are performed using a single feature and the performance of different features are compared. Both the k-nearest-neighbor (KNN) classifier and the support vector machine classifier (SVM) are employed. And for the KNN classifier, we use four different distance measures. Then, according to the classification results, three of these features with good performance are combined by simple concatenation. The combined feature is subsequently used for classification. This yields an overall comparison of the 13 features. Experiments on the very high resolution satellite images reveal that the combined feature consistently outperforms the other features and improves the results obtained.