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Synthetic Aperture Radar (SAR) images features clustering using Fuzzy cmeans (FCM) clustering algorithm

机译:使用模糊cmeans(FCM)聚类算法的合成孔径雷达(SAR)图像特征聚类

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Remote sensing applications such as Ecological monitoring, Disaster monitoring, Volcanic monitoring, surveillance and reconnaissance requires broad range imaginary data with very high resolution. Data captured under different times such as day or night and under different weather conditions poses adverse affects on retrieved results. Synthetic Aperture Radar (SAR) technology is used to mitigate such adverse effects. Recently SAR technology re-emerges because of the decrease in the cost of electronic components and tremendous advancement in computing power. This paper provides an application of Fuzzy c-means (FCM) clustering algorithm to SAR Images. The objective of this study is to segment various region of interest in remote sensing images for ecological monitoring.
机译:诸如生态监测,灾害监测,火山监测,监视和侦察之类的遥感应用需要高分辨率的大范围虚构数据。在白天或黑夜等不同时间和不同天气条件下捕获的数据会对检索结果造成不利影响。合成孔径雷达(SAR)技术用于减轻此类不利影响。近年来,由于电子组件成本的下降和计算能力的巨大进步,SAR技术重新出现。本文提出了一种模糊c均值聚类算法在SAR图像中的应用。这项研究的目的是分割遥感图像中的各个感兴趣区域,以进行生态监测。

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