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中文摘要：
高分辨率遥感影像中包含大量复杂的地物信息，直接通过分割提取道路的准确度往往较低，而且无法有效排除居民区等的干扰。提出一种结合视觉显著性分析的高分辨率遥感影像道路提取算法。该算法通过自适应阈值分割得到包含居民区和道路的特征图，利用人类视觉系统进行显著性分析，得到居民区的显著图，通过对显著图的分割得到只包含居民区的特征图，对两张特征图进行异或运算，即可提取出道路。实验结果表明，所提出的算法能较为有效地除去居民区的干扰，完整地提取出道路，对今后遥感图像道路提取有一定理论与实践意义。
英文摘要：
There is plenty of complex ground information in high-resolution remote sensing images. The direct road sementation in the images causes low accuracy and cannot rule out inferences such as residential areas. A road extraction method based on saliency analysis for high-resolution remote sensing images is proposed. The feature map of residential areas and roads is obtained by automatic seymentation. A saliency map of residential areas is obtained using the human visual system. The feature map of residential areas is generated by segmenting the saliency map. Finally, the roads are extracted by the logical exclusion OR operation of the two feature maps. Experimental results show that the proposed method can remove the inference of residential areas effectively and extract roads perfectly. It has both theoretical and practical significance for road extraction in remote sensing images in the future.
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