| dc.contributor.author | Chen, Y. | ru |
| dc.coverage.spatial | Минск | ru |
| dc.date.accessioned | 2026-01-23T05:56:11Z | |
| dc.date.available | 2026-01-23T05:56:11Z | |
| dc.date.issued | 2025 | |
| dc.identifier.citation | Chen, Y. Image enhancement techniques for satellite and UAV image matching / Y. Chen // Новые горизонты – 2025 : сборник материалов XII Белорусско-китайского молодежного инновационного форума, 27–28 ноября 2025 года / Белорусский национальный технический университет. – Минск : БНТУ, 2025. – Т. 1. – С. 62-63. | ru |
| dc.identifier.uri | https://rep.bntu.by/handle/data/163037 | |
| dc.description.abstract | Image enhancement plays a critical role in improving the accuracy and robustness of image matching between satellite and Unmanned Aerial Vehicle (UAV) imagery. Variations in resolution, illumination, and geometry between these two imaging modalities often hinder direct comparison. This paper reviews key traditional and deep learning–based enhancement algorithms used to address these challenges. It highlights how such methods improve feature extraction and matching accuracy and provides a concise overview of state-of-the-art approaches in this domain. | ru |
| dc.language.iso | en | ru |
| dc.publisher | БНТУ | ru |
| dc.title | Image enhancement techniques for satellite and UAV image matching | ru |
| dc.type | Working Paper | ru |