Hyperspectral image Target Detection based on Sparse Representation
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Updated
Sep 3, 2018 - MATLAB
Hyperspectral image Target Detection based on Sparse Representation
[ISPRS JP&RS 2018] Hyperspectral Image Classification via a Random Patches Network
Source code of "A Single Model CNN for Hyperspectral Image Denoising"
A deep learning-based method for hyperspectral image classification, which published in IEEE Trans. Geosci. Remote Sens., 2018.
Matlab code for Fusion of Dual Spatial Information for Hyperspectral Image Classification, 2020, TGRS
A Tutorial on Modeling and Inference in Undirected Graphical Models for Hyperspectral Image Analysis
Hyperspectral image classification by exploring deep tensor facorization, published in IGARSS 2018.
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.
A Novel Band Selection and Spatial Noise Reduction Method for Hyperspectral Image Classification, TGRS, 2022
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".
Code for KNN-based Representation of Superpixels for hyperspectral image classification
This code is for paper "Component Decomposition-Based Hyperspectral Resolution Enhancement for Mineral Mapping, Remote Sensing, 2020"
IEEE TGRS
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".
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.
An example of hyperspectral image classification using Matlab
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
Qingdao UAV-borne HSI (QUH) dataset for precise land cover classification.
This toolbox allows the implementation of the following diffusion-based clustering algorithms on synthetic and real datasets.
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