Application of a New Symmetry-Based Cluster Validity Index for Satellite Image Segmentation
Application of a New Symmetry-Based Cluster Validity Index for Satellite Image Segmentation
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DOI：
10.1109/lgrs.2008.915595
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发表时间：
2008-04
影响因子：
4.8
通讯作者：
S. Saha;S. Bandyopadhyay
中科院分区：
文献类型：
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作者：
S. Saha;S. Bandyopadhyay
图像分割的一个重要方法是根据像素的光谱特性对像素进行聚类。特别是，卫星图像包含土地覆盖类型，其中一些覆盖相当大的区域，而另一些（例如桥梁和道路）则占据相对较小的区域。自动检测大小差异如此之大的区域或簇是一项具有挑战性的任务。在这封信中，提出了一种基于对称性的聚类有效性指标，称为Sym-index（Symmetry distance-based index）。只要内部对称，它就能够正确指示不同大小的簇的存在。优化 Sym 索引的基于遗传算法的聚类技术用于自动确定聚类数量的图像分割。与其他指数相比，所提出的指数的优越性是为了从印度两个不同城市的 SPOT 和印度遥感卫星图像中自动分割土地覆盖类型。
An important approach for image segmentation is clustering pixels based on their spectral properties. In particular, satellite images contain land cover types, some of which cover significantly large areas, while some (e.g., bridges and roads) occupy relatively much smaller regions. Automatically detecting regions or clusters of such widely varying sizes presents a challenging task. In this letter, a symmetry-based cluster validity index, named Sym-index (Symmetry distance-based index), is proposed. It is able to correctly indicate the presence of clusters of different sizes as long as they are internally symmetrical. A genetic-algorithm-based clustering technique that optimizes the Sym-index is used for image segmentation where the number of clusters is determined automatically. The superiority of the proposed index, as compared to other indices, is established for automatically segmenting the land cover types from SPOT and Indian Remote Sensing satellite images of two different cities in India.