Numerical method for predictive estimate of classification efficiency for various cloud type images based on texture information from MODIS data

Vladimir G. Astafurov; Timofey V. Evsyutkin

doi:10.1117/12.2284314

30 November 2017 Numerical method for predictive estimate of classification efficiency for various cloud type images based on texture information from MODIS data

Vladimir G. Astafurov, Timofey V. Evsyutkin

Author Affiliations +

Proceedings Volume 10466, 23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics; 104664Y (2017) https://doi.org/10.1117/12.2284314
Event: XXIII International Symposium, Atmospheric and Ocean Optics, Atmospheric Physics, 2017, Irkutsk, Russian Federation

Abstract

A numerical method is proposed for constructing successive schemes for making decisions about the attribution of images of various cloud types to certain classes, which makes it possible to form sets of informative features and to evaluate their efficiency for subsequent classification. For formalized description of images, statistical methods of texture analysis are used: grey-level co-occurrence matrices, grey-level difference vectors, sum and difference histograms of image brightness levels, and statistical characteristics of individual pixel brightness. The results are discussed of the developed method testing for classification of 25 cloud types on MODIS images according to the current standard of the World Meteorological Organization. Recommendations are given for predictive estimate of classification efficiency of cloud cover images.

Citation Download Citation

Vladimir G. Astafurov and Timofey V. Evsyutkin "Numerical method for predictive estimate of classification efficiency for various cloud type images based on texture information from MODIS data", Proc. SPIE 10466, 23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 104664Y (30 November 2017); https://doi.org/10.1117/12.2284314

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