An Efficient Subspace Partition Method Using Curve Fitting for Hyperspectral Band Selection
Author:
Affiliation:
1. School of Automation, Xi’an University of Posts and Telecommunications, Xi’an, China
2. Northwest Institute of Nuclear Technology, Xi’an, China
3. School of Electronic Engineering, Xidian University, Xi’an, China
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/8859/10365397/10382646.pdf?arnumber=10382646
Reference12 articles.
1. Symmetrical Feature Propagation Network for Hyperspectral Image Super-Resolution
2. Deep Hashing Neural Networks for Hyperspectral Image Feature Extraction
3. A Fast Volume-Gradient-Based Band Selection Method for Hyperspectral Image
4. Supervised Band Selection Using Local Spatial Information for Hyperspectral Image
5. A Geometry-Based Band Selection Approach for Hyperspectral Image Analysis
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1. SSANet-BS: Spectral–Spatial Cross-Dimensional Attention Network for Hyperspectral Band Selection;Remote Sensing;2024-08-03
2. Structure-Preserved and Weakly Redundant Band Selection for Hyperspectral Imagery;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024
3. Joint Spatial and Spectral Graph-Based Consistent Self-Representation for Unsupervised Hyperspectral Band Selection;IEEE Transactions on Geoscience and Remote Sensing;2024
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