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A Novel Road Extraction Algorithm for High Resolution Remote Sensing Images |
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PP: 1435-1443 |
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Author(s) |
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Teng Xinpeng,
Song Shunlin,
Zhan Yongzhao,
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Abstract |
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Automatic road extraction from the high resolution remote sensing images is of great importance in intelligent transportation
and image processing. Hence, in this paper, an effective road extraction algorithm for high resolution remote sensing images based on
the circular projection transformation is proposed. The main idea of the proposed algorithm lies in that the road extraction results are
obtained by selecting a suitable initial template, and then search the matched templates through moving the initial template in two
directions. Firstly, the circular projection vector of the initial template is achieved by calculating the circular projection value at a
specific radius. Secondly, the optimal radius of the circle in circular projection transformation and the length of the seeking step and
the seeking angle are determined. Thirdly, for each seeking step the similarity between the target template and the initial template is
computed, and the template with the highest similarity is chosen. Finally, roads can be detected by the correct direction by exchanging
the first two detected points. To make performance evaluation, the IKONOS dataset is utilized and DMES and AUA algorithm are
compared. The experimental results demonstrate that the proposed algorithm can automatic the roads from high resolution remote
sensing images effectively and efficiently. |
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