Python module for hyperspectral image processing

Hyperspectral-Classification Pytorch

A keras based implementation of Hybrid-Spectral-Net as in IEEE GRSL paper "HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image Classification".

The official repo for [TPAMI'25] "HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model"

The repository contains the implementation of different machine learning techniques such as classification and clustering on Hyperspectral and Satellite Imagery.

Pytorch implementation of Multimodal Fusion Transformer for Remote Sensing Image Classification.

This is a tensorflow and keras based implementation of SSRNs in the IEEE T-GRS paper "Spectral-Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework".

Code of paper "Deep Learning Classifiers for Hyperspectral Imaging: A Review"

A2S2K-ResNet: Attention-Based Adaptive Spectral-Spatial Kernel ResNet for Hyperspectral Image Classification

Classification of the Hyperspectral Image Indian Pines with Convolutional Neural Network

Pytorch and Keras Implementations of Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects.

L. Sun, G. Zhao, Y. Zheng, and Z. Wu. "Spectral–Spatial Feature Tokenization Transformer for Hyperspectral Image Classification," in IEEE TGRS, 2022.

FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification (TGRS 2020) https://ieeexplore.ieee.org/document/9007624

A Fast Dense Spectral-Spatial Convolution Network Framework for Hyperspectral Images Classification(Remote Sensing 2018)

In this repository, You can find the files which implement dimensionality reduction on the hyperspectral image(Indian Pines) with classification.

Hyperspectral image Target Detection based on Sparse Representation

[IEEE TGRS 2018] Spectral-Spatial Unified Networks for Hyperspectral Image Classification

[Neural Networks 2025] Dual Selective Fusion Transformer Network for Hyperspectral Image Classification

Developing Low-Cost Multispectral Imagers using Inter-Band Redundancy Analysis and Greedy Spectral Selection in Hyperspectral Imaging. Remote Sensing 2021.

Measuring the ripeness of fruit with Hyperspectral Imaging and Deep Learning