Qingdao UAV-borne HSI (QUH) dataset for precise land cover classification.

SpaSSA: Superpixelwise Adaptive SSA for Unsupervised Spatial–Spectral Feature Extraction in Hyperspectral Image, TCYB, 2021

This toolbox allows the implementation of the following diffusion-based clustering algorithms on synthetic and real datasets.

IEEE TGRS

A Novel Band Selection and Spatial Noise Reduction Method for Hyperspectral Image Classification, TGRS, 2022

A Novel Spectral-Spatial Singular Spectrum Analysis Technique for Near Real-Time In Situ Feature Extraction in Hyperspectral Imaging, JSTARS, 2020

Hyper Spectral Image Classification using Machine Learning Methods

Fusion of PCA and Segmented-PCA Domain Multiscale 2-D-SSA for Effective Spectral-Spatial Feature Extraction and Data Classification in Hyperspectral Imagery, TGRS, 2020

This code is for paper "Component Decomposition-Based Hyperspectral Resolution Enhancement for Mineral Mapping, Remote Sensing, 2020"

Design and capture compressive measurements with those compressive measurements classification in performed.

Matlab code for Fusion of PCA and Segmented-PCA Domain Multiscale 2-D-SSA for Effective Spectral-Spatial Feature Extraction and Data Classification in Hyperspectral Imagery, IEEE TGRS, 2022

An example of hyperspectral image classification using Matlab

Ink Mismatch Detection using Convolutional Neural Networks

Code for KNN-based Representation of Superpixels for hyperspectral image classification

This toolbox allows the implementation of the Diffusion and Volume maximization-based Image Clustering algorithm for unsupervised hyperspectral image clustering. See "README.md" for more information. Copyright: Sam L. Polk, 2023.

The following demo comes for two papers "Spatial-prior generalized fuzziness extreme learning machine autoencoder-based active learning for hyperspectral image classification" and "Multi-layer Extreme Learning Machine-based Autoencoder for Hyperspectral Image Classification".

The demo partially associated with the following papers: "Spatial Prior Fuzziness Pool-Based Interactive Classification of Hyperspectral Images" and "Multiclass Non-Randomized Spectral–Spatial Active Learning for Hyperspectral Image Classification".

The code implementation of our paper "Deep Hashing Neural Networks for Hyperspectral Image Feature Extraction", GRSL, 2019

Multiscale Context-aware Ensemble Deep KELM for Efficient Hyperspectral Image Classification, TGRS, 2020.