YichuXu/PHDMamba

[IEEE GRSL 2025] PHDMamba: Progressive Hybrid Mamba for Hyperspectral Image Classification

28
/ 100
Experimental

This project helps remote sensing professionals classify land cover and materials using satellite or airborne hyperspectral images. It takes raw hyperspectral image cubes as input and outputs a classified map, highlighting different materials or land features. Geoscientists, urban planners, and environmental analysts can use this to understand surface composition.

Use this if you need to accurately identify and map different substances or land covers from complex hyperspectral imagery.

Not ideal if you are working with standard RGB images or require very rapid, on-the-fly classification without specialized deep learning setup.

hyperspectral-imaging remote-sensing land-classification environmental-monitoring geospatial-analysis
No Package No Dependents
Maintenance 10 / 25
Adoption 5 / 25
Maturity 13 / 25
Community 0 / 25

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13

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Language

Python

License

MIT

Last pushed

Jan 18, 2026

Commits (30d)

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