MICLUST: A CLUSTERING ALGORITHM FOR HIGH DIMENSIONAL DATA

被引：0

作者：

Jain, Namita ^{[1
]}

Ghosh, Susmita ^{[1
]}

Ientilucci, Emmett J. ^{[2
]}

机构：

[1] Jadavpur Univ, Dept Comp Sci, Kolkata, India

[2] Rochester Inst Technol, Digital Imaging & Remote Sensing Lab, Chester F Carlson Ctr Imaging Sci, Rochester, MN USA

来源：

IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2023年

关键词：

Unsupervised learning; mutual information; distance;

D O I：

10.1109/IGARSS52108.2023.10281575

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

This paper presents a method for identifying clusters in hyperspectral images. A new mutual information based similarity index named k-MIDI is proposed. This index, k-MIDI is used for hierarchical clustering of random samples from the data. The remaining observations are assigned to the clusters based on their nearest neighbours.

引用

页码：7280 / 7283

页数：4

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