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Hyperspectral Image Classification

Hyperspectral Image Classification is a task in the field of remote sensing and computer vision. It involves the classification of pixels in hyperspectral images into different classes based on their spectral signature. Hyperspectral images contain information about the reflectance of objects in hundreds of narrow, contiguous wavelength bands, making them useful for a wide range of applications, including mineral mapping, vegetation analysis, and urban land-use mapping. The goal of this task is to accurately identify and classify different types of objects in the image, such as soil, vegetation, water, and buildings, based on their spectral properties.

( Image credit: Shorten Spatial-spectral RNN with Parallel-GRU for Hyperspectral Image Classification )

Papers

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Showing 26–50 of 286 papers

TitleStatusHype
Correlation-Based Band Selection for Hyperspectral Image ClassificationCode0
MambaHSI: Spatial-Spectral Mamba for Hyperspectral Image ClassificationCode2
Discrete Wavelet Transform-Based Capsule Network for Hyperspectral Image Classification—0
DiffFormer: a Differential Spatial-Spectral Transformer for Hyperspectral Image ClassificationCode0
Hyperspectral Image Spectral-Spatial Feature Extraction via Tensor Principal Component Analysis—0
Dual-Branch Subpixel-Guided Network for Hyperspectral Image ClassificationCode1
Spectral-Spatial Transformer with Active Transfer Learning for Hyperspectral Image ClassificationCode1
Discrete Cosine Transform-Based Joint Spectral-Spatial Information Compression and Band Correlation Calculation for Hyperspectral Feature ExtractionCode0
IGroupSS-Mamba: Interval Group Spatial-Spectral Mamba for Hyperspectral Image Classification—0
Selective Transformer for Hyperspectral Image Classification—0
Hyperspectral Image Classification Based on Faster Residual Multi-branch Spiking Neural Network—0
Spatial-Aware Conformal Prediction for Trustworthy Hyperspectral Image ClassificationCode1
3D-RCNet: Learning from Transformer to Build a 3D Relational ConvNet for Hyperspectral Image ClassificationCode2
Multi-head Spatial-Spectral Mamba for Hyperspectral Image ClassificationCode0
Spatial and Spatial-Spectral Morphological Mamba for Hyperspectral Image ClassificationCode1
WaveMamba: Spatial-Spectral Wavelet Mamba for Hyperspectral Image Classification—0
Content-driven Magnitude-Derivative Spectrum Complementary Learning for Hyperspectral Image Classification—0
GraphMamba: An Efficient Graph Structure Learning Vision Mamba for Hyperspectral Image ClassificationCode1
Dual-stage Hyperspectral Image Classification Model with Spectral SupertokenCode1
HyperKAN: Kolmogorov-Arnold Networks make Hyperspectral Image Classificators SmarterCode1
Spectral Graph Reasoning Network for Hyperspectral Image Classification—0
How to Learn More? Exploring Kolmogorov-Arnold Networks for Hyperspectral Image ClassificationCode1
Boosting Hyperspectral Image Classification with Gate-Shift-Fuse Mechanisms in a Novel CNN-Transformer Approach—0
Multi-Teacher Multi-Objective Meta-Learning for Zero-Shot Hyperspectral Band Selection—0
Unveiling the Power of Wavelets: A Wavelet-based Kolmogorov-Arnold Network for Hyperspectral Image ClassificationCode2
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