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

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".

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

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

Classification of the Hyperspectral Image Indian Pines with Convolutional Neural Network

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

The official repo for the paper "HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model"

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

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

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

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

Source code of "Deep Pyramidal Residual Networks for Spectral–Spatial Hyperspectral Image Classification"

[ISPRS JP&RS 2018] Hyperspectral Image Classification via a Random Patches Network

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