An Unsupervised Hyperspectral Band Selection Method Based on Shared Nearest Neighbor and Correlation Analysis
Band selection is an important dimensionality reduction (DR) methodology for hyperspectral images (HSI). In recent years, many ranking-based clustering band selection methods have been developed. However, these methods do not consider the combination of bands in different clusters but only select th...
Main Authors: | Rongchao Yang, Jiangming Kan |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8937473/ |
Similar Items
-
An Efficient Clustering Method for Hyperspectral Optimal Band Selection via Shared Nearest Neighbor
by: Qiang Li, et al.
Published: (2019-02-01) -
Peak Density Clustering Algorithm Combining Natural and Shared Nearest Neighbor
by: BAI Exiang, LUO Ke, LUO Xiao
Published: (2021-05-01) -
Incremental Spectral Clustering with Closeness of Shared Nearest Neighbors
by: ZHAO Mengmeng, WANG Shitong
Published: (2020-06-01) -
Spectral–Spatial HyperspectralImage Classification With K-Nearest Neighbor and Guided Filter
by: Yanhui Guo, et al.
Published: (2018-01-01) -
EBARec-BS: Effective Band Attention Reconstruction Network for Hyperspectral Imagery Band Selection
by: Yufei Liu, et al.
Published: (2021-09-01)