KAIST-VICLab/C-DiffSET

Official repository of C-DiffSET

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This project helps defense analysts, environmental monitoring specialists, and disaster response teams interpret radar images more effectively. It takes Synthetic Aperture Radar (SAR) images, which can penetrate clouds and darkness, and converts them into realistic, visible-light Electro-Optical (EO) images. The output makes it easier to identify objects and features on the ground, improving situational awareness.

No commits in the last 6 months.

Use this if you need to transform radar imagery into clearer, camera-like images to identify ground objects, especially in conditions where traditional optical sensors are limited.

Not ideal if your primary need is real-time processing for dynamic environments, or if you require image translation for non-geospatial image types.

defense-intelligence environmental-monitoring disaster-response satellite-imagery remote-sensing
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 8 / 25

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Stars

21

Forks

2

Language

Python

License

MIT

Last pushed

Dec 09, 2024

Commits (30d)

0

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