Hyperspectral band selection via region-aware latent features fusion based clustering

Jun Wang; Chang Tang; Zhenglai Li; Xinwang Liu; Wei Emma Zhang; En Zhu; Lizhe Wang

doi:10.1016/j.inffus.2021.09.019

ScienceGate Book Chapters

JOURNAL ARTICLE

Hyperspectral band selection via region-aware latent features fusion based clustering

Jun Wang Chang Tang Zhenglai Li Xinwang Liu Wei Emma Zhang En Zhu Lizhe Wang

Year: 2021 Journal: Information Fusion Vol: 79 Pages: 162-173 Publisher: Elsevier BV

DOI: 10.1016/j.inffus.2021.09.019

Get Full-Text PDF Get Analytical Report

Keywords:

Hyperspectral imaging Computer science Pattern recognition (psychology) Artificial intelligence Cluster analysis Redundancy (engineering) Segmentation Feature selection

Metrics

Cited By

5.33

FWCI (Field Weighted Citation Impact)

Refs

0.96

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Remote-Sensing Image Classification

Physical Sciences → Engineering → Media Technology

Advanced Image Fusion Techniques

Physical Sciences → Engineering → Media Technology

Remote Sensing and Land Use

Physical Sciences → Earth and Planetary Sciences → Atmospheric Science

Hyperspectral band selection via region-aware latent features fusion based clustering

Metrics

Citation History

Topics

Related Documents

Region-Aware Hierarchical Latent Feature Representation Learning-Guided Clustering for Hyperspectral Band Selection

Hyperspectral band selection via region-wise latent feature fusion and graph filter embedded subspace clustering

Tensor Decomposition Based Latent Feature Clustering for Hyperspectral Band Selection

Hyperspectral Band Selection via Spatial-Spectral Weighted Region-wise Multiple Graph Fusion-Based Spectral Clustering

Latent Feature Representation-Based Low Rank Subspace Clustering for Hyperspectral Band Selection