Partitioned Relief-F Method for Dimensionality Reduction of Hyperspectral Images
The classification of hyperspectral remote sensing images is difficult due to the curse of dimensionality. Therefore, it is necessary to find an effective way to reduce the dimensions of such images. The Relief-F method has been introduced for supervising dimensionality reduction, but the band subse...
Main Authors: | Jiansi Ren, Ruoxiang Wang, Gang Liu, Ruyi Feng, Yuanni Wang, Wei Wu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-03-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/12/7/1104 |
Similar Items
-
An SVM-Based Nested Sliding Window Approach for Spectral–Spatial Classification of Hyperspectral Images
by: Jiansi Ren, et al.
Published: (2020-12-01) -
Investigation on methods for dimensionality reduction on hyperspectral image data
by: Robin T. Clarke, et al.
Published: (2005-04-01) -
Strategies for dimensionality reduction in hyperspectral remote sensing: A comprehensive overview
by: Radhesyam Vaddi, et al.
Published: (2024-03-01) -
Feature Selection for Cross-Scene Hyperspectral Image Classification Using Cross-Domain I-ReliefF
by: Chengjie Zhang, et al.
Published: (2021-01-01) -
An outlook: machine learning in hyperspectral image classification and dimensionality reduction techniques
by: Tatireddy Subba Reddy, et al.
Published: (2022-01-01)