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Segmentation of Multi-spectral Satellite Images Based on Watershed Algorithm

机译:基于分水岭算法的多光谱卫星图像分割

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In this paper, a two-step segmentation algorithm is proposed based on watershed transform to segment multi-spectral satellite images. The first step is to use watershed segmentation to gain the initial over-segmented regions and the next one is region merging using a strategy of minimizing the overall heterogeneity increased within segments at each merging step. Textural, color and shape information of segments is used in the merging process. The study was conducted to explore an efficient approach to segment remote sensing images especially for high resolution multi-spectral satellite imagery. Experimental results show that the proposed method can produce quite good segmentation results and is very promising in segmentation of remotely sensing imagery in the future.
机译:本文基于流域变换提出了一种两步分割算法,分段多谱卫星图像。第一步是使用流域分割来获得初始过分区分区域,并且下一个是使用最小化每个合并步骤的段内的总体异质性的策略来合并的区域合并。段的纹理,颜色和形状信息用于合并过程中。进行该研究以探讨侦察遥感图像的有效方法,尤其是高分辨率多光谱卫星图像。实验结果表明,该方法可以产生相当良好的细分结果,并且在未来远程感应图像的分割方面非常有前景。

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