Hyperspectral Dimensionality Reduction Based on Multiscale Superpixelwise Kernel Principal Component Analysis

Hyperspectral Dimensionality Reduction Based on Multiscale Superpixelwise Kernel Principal Component Analysis

Dimensionality reduction (DR) is an important preprocessing step in hyperspectral image applications. In this paper, a superpixelwise kernel principal component analysis (SuperKPCA) method for DR that performs kernel principal component analysis (KPCA) on each homogeneous region is proposed to fully...

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Bibliographic Details
Main Authors:	Lan Zhang, Hongjun Su, Jingwei Shen
Format:	Article
Language:	English
Published:	MDPI AG 2019-05-01
Series:	Remote Sensing
Subjects:	unsupervised dimensionality reduction superpixel segmentation kernel principal component analysis (KPCA) fundamental image hyperspectral image (HSI)
Online Access:	https://www.mdpi.com/2072-4292/11/10/1219

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