摘要
Accurate digital orthophoto map generation from high-resolution aerial images is important in various applications. Compared with the existing commercial software and the current state-of-the-art mosaicing systems, a novel fast georeferenced orthophoto mosaicing framework is proposed in this study. The framework can adapt to the challenging requirements of high-accuracy orthoimage generations with relatively fast speed, even if the overlap rate is low. We provide appearance and spatial correlation-constrained fast low-overlap neighbor candidate query and matching. On the basis of GPS information, we introduce an absolute position and rotation-averaging strategy for global pose initialization, which is essential for the high convergence and efficiency of nonconvex pose optimization of every image. We also propose a planar-restricted global pose graph optimization method. The optimization is extremely efficient and robust considering that point clouds are parameterized to planes. Finally, we apply a matching graph-based exposure compensation and region reduction algorithm for large-scale and high-resolution image fusion with high efficiency and novel precision. Experimental results demonstrate that our method can achieve the state-of-the-art performance while maintaining high precision and robustness.
源语言 | 英语 |
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文章编号 | 9147004 |
页(从-至) | 3502-3517 |
页数 | 16 |
期刊 | IEEE Transactions on Geoscience and Remote Sensing |
卷 | 59 |
期 | 4 |
DOI | |
出版状态 | 已出版 - 4月 2021 |