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Using a Model of a Spatial–Hierarchical Quadtree with Truncated Branches to Improve the Accuracy of Image Classification

  • METHODS AND TOOLS FOR PROCESSING AND INTERPRETING SPACE INFORMATION
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Abstract

This article considers the problem of increasing the accuracy of classifying satellite image samples under the assumption that their samples are independent. The increase in accuracy is achieved by additional processing of the image as a spatially hierarchical quadtree, which is a type of random Markov field. A modification of this model is proposed: a spatially hierarchical quadtree with truncated branches. For the original and modified models, we compare the classification results of a real radar image characterized by a large amount of noise. The classification accuracy is estimated as the proportion of correctly classified pixels within the selected homogeneous areas. It has been established that, within the framework of the modified model, homogeneous areas of images are more correctly classified by transferring the properties of accumulated images of the same region to them. The modified model makes it possible to obtain a classification result of higher accuracy than the original one when processing noisy images, while having less resource intensity.

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Funding

This work was supported by ongoing institutional funding. No additional grants to carry out or direct this particular research were obtained.

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Authors and Affiliations

  1. AO Kontsern Morinformsistema-Agat, Moscow, Russia

    A. M. Dostovalova

  2. Federal Research Center “Computer Science and Control” of the Russian Academy of ScienceFRC (CSC RAS), Moscow, Russia

    A. M. Dostovalova

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  1. A. M. Dostovalova
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Correspondence to A. M. Dostovalova.

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Dostovalova, A.M. Using a Model of a Spatial–Hierarchical Quadtree with Truncated Branches to Improve the Accuracy of Image Classification. Izv. Atmos. Ocean. Phys. 59, 1255–1262 (2023). https://doi.org/10.1134/S0001433823120071

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  • DOI: https://doi.org/10.1134/S0001433823120071

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