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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Coastline Extraction From High-Resolution Multispectral Images by Integrating Prior Edge Information With Active Contour Model
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Coastline Extraction From High-Resolution Multispectral Images by Integrating Prior Edge Information With Active Contour Model

机译:通过将先验边缘信息与主动轮廓模型集成,从高分辨率多光谱图像中提取海岸线

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摘要

Monitoring coastlines is essential for scientific protection and utilization of coastal zones. Since it is very common that various types of coasts are intermixed, there is much practical significance to propose a method that has universality. Moreover, weak edges and sea noise are the main problems of coastline delineation with high-resolution multispectral imagery. To settle these problems, a new method integrating prior edge information with an edge-based active contour model (EI-ACM) is proposed in this article. First, the coarse sea region is obtained with a novel region growth method. An edge refining process is then proposed to refine the edges detected by the Canny operator and obtain the prior edge information. The prior edge information is subsequently integrated with an EL-ACM to guide its evolution. Finally, the coastline is obtained by contour evolution. To validate the proposed method, it was compared to the state-of-the-art coastline extraction method. The results proved that the proposed EI-ACM outperforms in weak edge retention and avoiding the interference of sea noise, while being robust to various type of coastal.
机译:监测海岸线对于科学保护和利用沿海地区至关重要。由于将各种类型的海岸混合在一起是非常普遍的,因此提出一种具有通用性的方法具有许多实际意义。此外,边缘薄弱和海噪声是高分辨率多光谱图像在海岸线描绘中的主要问题。为了解决这些问题,本文提出了一种将先验边缘信息与基于边缘的主动轮廓模型(EI-ACM)相集成的新方法。首先,用新颖的区域生长方法获得粗海区域。然后提出边缘细化处理以细化Canny算子检测到的边缘并获得先验边缘信息。先验边缘信息随后与EL-ACM集成在一起,以指导其发展。最后,通过轮廓演化获得海岸线。为了验证所提出的方法,将其与最新的海岸线提取方法进行了比较。结果证明,所提出的EI-ACM在弱边缘保持性和避免海噪声干扰方面表现出色,同时对各种类型的海岸都具有鲁棒性。

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