TY - GEN
T1 - ROAD EXTRACTION FROM SATELLITE IMAGE VIA AUXILIARY ROAD LOCATION PREDICTION
AU - Hu, Jingtao
AU - Wang, Qi
AU - Li, Xuelong
N1 - Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - Road extraction from satellite images is usually corrupted with several disconnected segments so that it does not satisfy the real application. The segmentation-based methods fail to correct separated roads due to the incompleteness information. Therefore, this paper introduces auxiliary Road Location Prediction(RLP), a task leveraging global context information to help road segmentation infer each road segment. The auxiliary task has two branches: horizontal location prediction and vertical location prediction which can predict locations of all the roads. By combining road segmentation and RLP, road extraction performance is effectively improved. As a result, the additional training signals help the primary road segmentation task to aggregate surrounding scene information to reason about its connectivity. The experiments on two public datasets have demonstrated the effectiveness of the proposed method.
AB - Road extraction from satellite images is usually corrupted with several disconnected segments so that it does not satisfy the real application. The segmentation-based methods fail to correct separated roads due to the incompleteness information. Therefore, this paper introduces auxiliary Road Location Prediction(RLP), a task leveraging global context information to help road segmentation infer each road segment. The auxiliary task has two branches: horizontal location prediction and vertical location prediction which can predict locations of all the roads. By combining road segmentation and RLP, road extraction performance is effectively improved. As a result, the additional training signals help the primary road segmentation task to aggregate surrounding scene information to reason about its connectivity. The experiments on two public datasets have demonstrated the effectiveness of the proposed method.
KW - auxiliary task
KW - global context feature
KW - Road extraction
KW - road location prediction
UR - https://www.scopus.com/pages/publications/85129896054
U2 - 10.1109/IGARSS47720.2021.9554086
DO - 10.1109/IGARSS47720.2021.9554086
M3 - 会议稿件
AN - SCOPUS:85129896054
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2182
EP - 2185
BT - IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
Y2 - 12 July 2021 through 16 July 2021
ER -