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...

Full description

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

Internet

https://www.mdpi.com/2072-4292/11/10/1219

Similar Items