A semantic feature extraction method for multitemporal high resolution aerial image registration is proposed in this paper. These features encode properties or information about temporally invariant objects such as roads and help deal with issues such as changing foliage in image registration, which classical handcrafted features are unable to address. These features are extracted from a semantic segmentation network and have shown good robustness and accuracy in registering aerial images across years and seasons in the experiments.
CITATION STYLE
Gupta, A., Peng, Y., Watson, S., & Yin, H. (2019). Multitemporal Aerial Image Registration Using Semantic Features. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11872 LNCS, pp. 78–86). Springer. https://doi.org/10.1007/978-3-030-33617-2_9
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