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Классификация методов сегментации снимков земной поверхности
https://doi.org/10.21122/2309-4923-2023-4-20-28
Аннотация
В данной работе представлена классификация методов сегментации снимков земной поверхности. Рассмотрены такие подходы как сравнение с шаблоном, машинное обучение и глубокие нейронные сети, а также применение знаний об анализируемых объектах. Рассмотрены особенности применения вегетационных индексов для сегментации данных по спутниковым снимкам. Отмечены преимущества и недостатки. Систематизированы результаты, полученные авторами методик, появившихся за последние 10 лет, что позволит заинтересованным быстрее сориентироваться, сформировать идеи для последующих исследований.
Об авторах
Д. B. КуприяноваБеларусь
Старший преподаватель, аспирант, кафедра электронных вычислительных машин
г. Минск
Д. Ю. Перцев
Беларусь
Кандидат технических наук, доцент, доцент кафедры электронных вычислительных машин
г. Минск
М. М. Татур
Россия
Доктор технических наук, профессор, профессор кафедры электронных вычислительных машин
г. Минск
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Дополнительные файлы
Для цитирования: Куприянова Д.B., Перцев Д.Ю., Татур М.М. Классификация методов сегментации снимков земной поверхности. «Системный анализ и прикладная информатика». 2023;(4):20-28. https://doi.org/10.21122/2309-4923-2023-4-20-28
For citation: Kypriyanava D.V., Pertsau D.Y., Tatur M.M. Classification of earth surface image segmentation methods. «System analysis and applied information science». 2023;(4):20-28. (In Russ.) https://doi.org/10.21122/2309-4923-2023-4-20-28
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