This article proposes a method for interpreting multispectral images based on classification algorithms using wavelet features and their quantization. The features are transformed into binary vectors through value range segmentation, followed by decision-making using class membership estimation. A distinctive aspect of the approach is the introduction of a feature significance indicator that considers the discriminative power of the characteristics and is used both as a selection criterion and as a weighting factor.
| Mualliflar | Сеитназаров, К.К., Куралбаев, А.О., Султанбаева, А.Т., Султанов, Б.К. |
|---|---|
| Jurnal | Ilim ha’m ja’miyet |
| Nashr sanasi | 2025-08-15 |
| Son | 5-1 |
| Betlar | 14-17 |
| Til | Rus |
кўп зонали тасвирлар, классификация, белгиларни квантлаш, иккилик векторлар, вейвлет-трансформация, оғирлик коеффициентлари, аҳамият кўрсаткичи, масофавий зондлаш интерпретацияси, многозональные изображения, классификация, квантование признаков, бинарные векторы, вейвлет-преобразование, весовые коэффициенты, показатель значимости, интерпретация ДЗЗ, multispectral images, classification, feature quantization, binary vectors, wavelet transform, weighting coefficients, significance indicator, remote sensing interpretation
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