Segmentation of Natural and Anthropogenic Objects by Panchromatic Satellite Images Using Statistical Textural Features

The problem of segmentation of natural and technogenic objects by panchromatic satellite images of ultra-high spatial resolution (<1 m) using texture analysis is considered. The effectiveness of various statistical methods for extracting textural features is analyzed. On the basis of numerical experiments, methods have been identified that make it possible to segment with high accuracy (>95%) the main types of natural and anthropogenic objects, as well as various structures of the plant canopy. The TTSPCA method is proposed, which makes it possible to share the most informative features extracted using various statistical methods. The results of test calculations show that this method has higher accuracy (>99%) in solving the problem of texture segmentation compared to the considered standard approaches.