Hyperspectral-Classification

Classification of different landcover classes using Hyperspectral data.

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Steps to Run:

1. Create a virtual environment using command: virtualenv myenv
2. Activate the virtual environment: source venv/bin/activate
3. Install the requirements file: pip install -r requirements.txt
4. Download this gulfport mat file in the same directory.
5. Run the file: python main.py

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Results:

An accuracy of 87.98% ± 0.71 was achieved with Fully connected neural network. The Confusion matrix is shown below:

References

P. Gader, A. Zare, R. Close, J. Aitken, G. Tuell, “MUUFL Gulfport Hyperspectral and LiDAR Airborne Data Set,” University of Florida, Gainesville, FL, Tech. Rep. REP-2013-570, Oct. 2013.

X. Du and A. Zare, “Technical Report: Scene Label Ground Truth Map for MUUFL Gulfport Data Set,” University of Florida, Gainesville, FL, Tech. Rep. 20170417, Apr. 2017.

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