Рақамли технологияларнинг назарий ва амалий масалалари Volume 8 Issue 1 (2025) · pp. 7-21
Algorithms for scene classification in remote sensing images based on low- and mid-level descriptors
Yusupov, O.R., Xandamov, Y.X., Eshonqulov, E.Sh.
Abstract
Scene classification is one of the important tasks in the analysis of remote sensing images. This article examines the application of machine learning algorithms for forming image descriptors and classifying scenes. Within the scope of the study, low-, mid-, and high-level descriptors were used, including Local Binary Pattern (LBP), Histogram of Oriented Gradients (HOG), Scale-Invariant Feature Transform (SIFT), Oriented FAST and Rotated BRIEF (ORB), BRISK, and BRIEF descriptors. For scene classification, SVM, Random Forest, Decision Tree, Naive Bayes, kNN, and Logistic Regression algorithms were employed. The results of the study demonstrated the effectiveness of the combinations of descriptors and classifiers, with the SIFT descriptor providing the best results. However, the overall results indicated the need to improve methods to achieve higher accuracy in scene classification. This study explores the development and application of algorithms based on low- and mid-level descriptors for scene classification in remote sensing images. For accurate image classification, it is important to form descriptors that express key attributes (such as image dimensions and formats), visual features (such as color and textures), semantic information (contextual relationships), and geometric consistency. The study consists of two main stages: feature extraction and training a classifier based on machine learning algorithms (kNN, Naive Bayes, Random Forest, SVM, and Logistic Regression). The study was conducted on the NWPU-RESISC45 dataset, and classification was performed across 45 different scene categories. The results show that SIFT and other descriptors possess high accuracy, but further research is required to improve classification performance.
sahnali tasniflashmasofaviy zondlash tasviribelgilardeskritorklassifikatorNWPU-RESISC45scene classificationremote sensing imagefeaturedescriptor
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