A toolbox for spectral compressive imaging reconstruction including MST (CVPR 2022), CST (ECCV 2022), DAUHST (NeurIPS 2022), BiSCI (NeurIPS 2023), HDNet (CVPR 2022), MST++ (CVPRW 2022), etc.
Hyperspectral-Classification Pytorch
The repository contains the implementation of different machine learning techniques such as classification and clustering on Hyperspectral and Satellite Imagery.
🖼️ A tool for efficient processing of spectral images with Python.
Band-Adaptive Spectral-Spatial Feature Learning Deep Neural Network for Hyperspectral Image Classification
Gaussian processes and Bayesian optimization for images and hyperspectral data
Alternately Updated Convolutional Spectral-Spatial Network for Hyperspectral Image Classification(Remote Sensing 2019)
This demo implements FRFE-RX destriping for HSI
Hyperspectral Unmixing via Dual Attention Convolutional Neural Networks | 基于双注意力卷积神经网络的高光谱图像解混
Hyperspectral Band Selection using Self-Representation Learning with Sparse 1D-Operational Autoencoder (SRL-SOA)
Hyperspectral Pansharpening: Critical Review, Tools and Future Perspectives
This is the raw source code of the paper 'Enhancing Hyperspectral Images via Diffusion Model and Group-Autoencoder Super-Resolution Network'
An R package to simplify working with NEON's hyperspectral imagery
Independent component analysis for dimensionality reduction of hyperspectral images
A superpixel-based relational auto-encoder for feature extraction of hyperspectral images
A simple and light CNN-based regression model for soil parameters estimation from hyperspectral images.
A complete solution to utilise both spatial and spectral information in the classification process is provided by the integration of deep CNNs with PCA for feature extraction and dimensionality reduction.
Spectral Clustering on the Sparse Coefficients of Learned Dictionaries - Published in SIVP
[AAAI2024] This the implementation of Dual-Window Multiscale Transformer for Hyperspectral Snapshot Compressive Imaging.
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