Partitioned Relief-F Method for Dimensionality Reduction of Hyperspectral Images

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...

Full description

Bibliographic Details
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:	dimensionality reduction feature selection partitioned relief-f hyperspectral remote sensing
Online Access:	https://www.mdpi.com/2072-4292/12/7/1104

Similar Items

Investigation on methods for dimensionality reduction on hyperspectral image data
by: Robin T. Clarke, et al.
Published: (2005-04-01)

An SVM-Based Nested Sliding Window Approach for Spectral–Spatial Classification of Hyperspectral Images
by: Jiansi Ren, et al.
Published: (2021-12-01)

Dimensionality reduction method for hyperspectral image analysis based on rough set theory
by: Zhenhua Wang, et al.
Published: (2020-01-01)

Dimensionality reduction method for hyperspectral images based on weighted spatial-spectral combined preserving embedding
by: HUANG Hong, et al.
Published: (2019-08-01)

Feature Selection for Cross-Scene Hyperspectral Image Classification Using Cross-Domain I-ReliefF
by: Chengjie Zhang, et al.
Published: (2021-01-01)

Investigating the Effects of a Combined Spatial and Spectral Dimensionality Reduction Approach for Aerial Hyperspectral Target Detection Applications
by: Fraser Macfarlane, et al.
Published: (2021-04-01)

Spatial-Spectral Multiple Manifold Discriminant Analysis for Dimensionality Reduction of Hyperspectral Imagery
by: Guangyao Shi, et al.
Published: (2019-10-01)

Review on graph learning for dimensionality reduction of hyperspectral image
by: Liangpei Zhang, et al.
Published: (2020-01-01)

Dimensionality Reduction of Hyperspectral Image Using Spatial-Spectral Regularized Sparse Hypergraph Embedding
by: Hong Huang, et al.
Published: (2019-05-01)

Band Priority Index: A Feature Selection Framework for Hyperspectral Imagery
by: Wenqiang Zhang, et al.
Published: (2018-07-01)

Impact of linear dimensionality reduction methods on the performance of anomaly detection algorithms in hyperspectral images
by: Mohsen Zare-Baghbidi, et al.
Published: (2015-01-01)

Tensor Based Multiscale Low Rank Decomposition for Hyperspectral Images Dimensionality Reduction
by: Jinliang An, et al.
Published: (2019-06-01)

Band Selection-Based Dimensionality Reduction for Change Detection in Multi-Temporal Hyperspectral Images
by: Sicong Liu, et al.
Published: (2017-09-01)

Dimensionality reduction of hyperspectral images of vegetation and crops based on self-organized maps
by: David Ruiz Hidalgo, et al.
Published: (2021-06-01)

Tensor Discriminant Analysis via Compact Feature Representation for Hyperspectral Images Dimensionality Reduction
by: Jinliang An, et al.
Published: (2019-08-01)

Dimensionality Reduction of Hyperspectral Image with Graph-Based Discriminant Analysis Considering Spectral Similarity
by: Fubiao Feng, et al.
Published: (2017-03-01)

Spectral transformation based on nonlinear principal component analysis for dimensionality reduction of hyperspectral images
by: Giorgio Licciardi, et al.
Published: (2018-01-01)

Global tests of P-values for multifactor dimensionality reduction models in selection of optimal number of target genes
by: Dai Hongying, et al.
Published: (2012-05-01)

Spectral-Locational-Spatial Manifold Learning for Hyperspectral Images Dimensionality Reduction
by: Na Li, et al.
Published: (2021-07-01)

Deep Fully Convolutional Embedding Networks for Hyperspectral Images Dimensionality Reduction
by: Na Li, et al.
Published: (2021-02-01)

Hyperspectral Dimensionality Reduction by Tensor Sparse and Low-Rank Graph-Based Discriminant Analysis
by: Lei Pan, et al.
Published: (2017-05-01)

Pairwise-Distance-Analysis-Driven Dimensionality Reduction Model with Double Mappings for Hyperspectral Image Visualization
by: Yi Long, et al.
Published: (2015-06-01)

Multi-Feature Manifold Discriminant Analysis for Hyperspectral Image Classification
by: Hong Huang, et al.
Published: (2019-03-01)

Evaluating Variable Selection and Machine Learning Algorithms for Estimating Forest Heights by Combining Lidar and Hyperspectral Data
by: Sanjiwana Arjasakusuma, et al.
Published: (2020-08-01)

A new kernel method for hyperspectral image feature extraction
by: Bin Zhao, et al.
Published: (2017-10-01)

Local Geometric Structure Feature for Dimensionality Reduction of Hyperspectral Imagery
by: Fulin Luo, et al.
Published: (2017-08-01)

Supervised Dimensionality Reduction of Hyperspectral Imagery Via Local and Global Sparse Representation
by: Faxian Cao, et al.
Published: (2021-01-01)

Clustering based feature selection using Partitioning Around Medoids (PAM)
by: Dewi Pramudi Ismi, et al.
Published: (2020-05-01)

CSR-Net: Camera Spectral Response Network for Dimensionality Reduction and Classification in Hyperspectral Imagery
by: Yunhao Zou, et al.
Published: (2020-10-01)

Semisupervised Hypergraph Discriminant Learning for Dimensionality Reduction of Hyperspectral Image
by: Fulin Luo, et al.
Published: (2020-01-01)

Hyperspectral Image Classification via Slice Sparse Coding Tensor Based Classifier With Compressive Dimensionality Reduction
by: Lixia Yang, et al.
Published: (2020-01-01)

Discovering the Representative Subset with Low Redundancy for Hyperspectral Feature Selection
by: Wenqiang Zhang, et al.
Published: (2019-06-01)

Using spatial-spectral regularized hypergraph embedding for hyperspectral image classification
by: HUANG Hong, et al.
Published: (2019-06-01)

Dimensionality Reduction of Hyperspectral Image Based on Local Constrained Manifold Structure Collaborative Preserving Embedding
by: Guangyao Shi, et al.
Published: (2021-04-01)

Extended Subspace Projection Upon Sample Augmentation Based on Global Spatial and Local Spectral Similarity for Hyperspectral Imagery Classification
by: Jiaochan Hu, et al.
Published: (2021-01-01)

Feature reduction of hyperspectral images: Discriminant analysis and the first principal component
by: Maryam Imani, et al.
Published: (2015-01-01)

Learning a Robust Local Manifold Representation for Hyperspectral Dimensionality Reduction
by: Danfeng Hong, et al.
Published: (2017-01-01)

Spatial and Spectral Nonparametric Linear Feature Extraction Method for Hyperspectral Image Classification
by: Jinn-Min Yang, et al.
Published: (2017-07-01)

Comparison of swarm intelligence algorithms for optimized band selection of hyperspectral remote sensing image
by: Xiaohui Ding, et al.
Published: (2020-07-01)

An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery
by: JongCheol Pyo, et al.
Published: (2020-03-01)