ROBUST ROAD DETECTION ON HIGH-RESOLUTION REMOTE SENSING IMAGES WITH OCCLUSION BY A DUAL-DECODED UNET

It is challenging to perform robust road detection on remote sensing images in a complex scene with occlusions by plants and buildings. In this paper, an elaborate dual-decoded U-Net combined with atrous spatial pyramid pooling is proposed to tackle this scenario. In the proposed network, a dual-decoder structure is designed, where a small decoder aims to extract the attention information and it is delivered to the other decoder to enhance the context. Finally, the proposed method is verified on the DeepGlobe dataset. The experiment results demonstrate that the proposed method outperforms other compared methods.