  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.
