Fuzzy C-Means Technique for Band Reduction and Segmentation of Hyperspectral Satellite Image

V. S. Kumar, Kavitha M. Saravanan, S. BalaramV.V.S.S., S. Sivaprakasam
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引用次数: 1

Abstract

This paper put forward for the segmentation process on the hyperspectral remote sensing satellite scene. The prevailing algorithm, fuzzy c-means, is performed on this scene. Moreover, this algorithm is performed in both inter band as well as intra band clustering (i.e., band reduction and segmentation are performed by this algorithm). Furthermore, a band that has topmost variance is selected from every cluster. This structure diminishes these bands into three bands. This reduced band is de-correlated, and subsequently segmentation is carried out using this fuzzy algorithm.
高光谱卫星图像的模糊c均值减带分割技术
提出了用于高光谱遥感卫星场景的分割过程。目前流行的算法,模糊c-means,在这个场景中执行。此外,该算法既可以进行带间聚类,也可以进行带内聚类(即通过该算法进行带缩减和分割)。然后,从每个聚类中选择方差最大的波段。这种结构将这些波段缩小为三个波段。将压缩后的波段去相关,然后使用该模糊算法进行分割。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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