Comparative studies of 3-D textural features and their reliability in terrain classification

We study the reliability of a set of stereo-based 3-D textural features in classification in response to different training data. Two types of training data, “labeling-based” and “chip-based,” are investigated. Experiments have been carried out to compare the 3-D features with a set of 2-D features based on co-occurrence analysis. Results show that the 3-D features consistently outperform the 2-D features in terms of classification accuracy under various configurations of training data