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Spectral clustering employs spectral-graph structure of a similarity matrix to partition data into disjoint meaningful groups, because of its well-defined mathematical framework, good performance and simplicity, spectral clustering has gained considerable attentions in the recent past. Despite these virtues, it suffers from several drawbacks, such as it is unable to determine a reasonable cluster...
Aiming for the feature of low resolution and faint contrast for infrared image, a segmentation algorithm is presented based on the neighborhood weight fuzzy c-means kernel clustering. By using the Gaussian kernel in target function, the traditional euclidean distance in the FCM is replaced by a kernel-induced distance. At the same time, this method computes the sample weight during the clustering...
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