| Issue |
E3S Web Conf.
Volume 223, 2020
Regional Problems of Earth Remote Sensing (RPERS 2020)
|
|
|---|---|---|
| Article Number | 02013 | |
| Number of page(s) | 7 | |
| Section | Models and Methods of Remote Sensing Data Processing | |
| DOI | https://doi.org/10.1051/e3sconf/202022302013 | |
| Published online | 21 December 2020 | |
Information content of statistical texture features in the problem of recognition and mapping of natural and man-made objects from space images
1 Marchuk Institute of Numerical Mathematics of Russian Academy of Sciences, ul. Gubkina 8, 119333 Moscow, Russia
2 Moscow Institute of Physics and Technology (National Research University), 9 Institutskiy per., Dolgoprudny, Moscow Region, 141701, Russia
3 Laboratoire de PhysicoChimie de l'Atmosphère Université du Littoral Cote d'Opale, Avenue Maurice Schumann 189A, 59140 Dunkerque, France
4 Federal State Budgetary Educational Institution of Higher Education “Bauman Moscow State Technical University (National Research University) ”, 105005, Moscow, 2nd Baumanskaya st. 5, bld. 1.
Statistical texture features are frequently used for the thematic processing of very high spatial resolution satellite images. The assessment of information content of 1st and 2nd order statistics is carried out based on processing WorldView-2 images of test areas located on the territory of the Savvatyevskoe forestry and employing the corresponding ground-based data. The comparison of the accuracy and computational efficiency of traditional and ensemble classifiers in the problem of pattern recognition of various natural and man-made objects reveals the high performance of the error correcting output codes method. The estimates obtained in this study demonstrate the advantage of using ensemble classification and 2nd order statistical texture features.
© The Authors, published by EDP Sciences, 2020
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