Boundary-Aware Dual-Stream Network for VHR Remote Sensing Images Semantic Segmentation
Semantic segmentation for very-high-resolution remote sensing images has been a research hotspot in the field of remote sensing image analysis. However, most existing methods still suffer from a challenge that object boundaries cannot be finely recovered. To tackle the problem, we develop a dual-str...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9416898/ |
| Summary: | Semantic segmentation for very-high-resolution remote sensing images has been a research hotspot in the field of remote sensing image analysis. However, most existing methods still suffer from a challenge that object boundaries cannot be finely recovered. To tackle the problem, we develop a dual-stream network based on the U-Net architecture, Instead of the traditional skip connections, a boundary attention module is proposed to introduce the boundary information from the EDN module to the SSN module. Experiments on ISPRS Potsdam and Vaihingen datasets show the effectiveness of the proposed network, especially in man-made objects with distinct boundaries. |
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| ISSN: | 2151-1535 |