https://github.com/tanyakuznetsova/image-restoration-with-gibbs-sampler
Reconstructing a black and white Japanese woodblock print using Bayesian inference
https://github.com/tanyakuznetsova/image-restoration-with-gibbs-sampler
bayesian-inference gibbs-sampler gibbs-sampling gibbs-sampling-algorithm image-denoising image-processing unsupervised-learning unsupervised-machine-learning
Last synced: 8 months ago
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Reconstructing a black and white Japanese woodblock print using Bayesian inference
- Host: GitHub
- URL: https://github.com/tanyakuznetsova/image-restoration-with-gibbs-sampler
- Owner: tanyakuznetsova
- Created: 2024-01-04T17:09:43.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-01-05T13:04:11.000Z (almost 2 years ago)
- Last Synced: 2025-01-18T08:36:25.820Z (9 months ago)
- Topics: bayesian-inference, gibbs-sampler, gibbs-sampling, gibbs-sampling-algorithm, image-denoising, image-processing, unsupervised-learning, unsupervised-machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 1.28 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Image Restoration with Gibbs Sampler
This project explores the application of Gibbs sampling for image restoration.
The goal is to denoise corrupted images using a Gibbs sampling algorithm.
The implementation is done in Python with NumPy, OpenCV, and matplotlib.
Feel free to explore the code and experiment with different parameters for image restoration.
## Acknowledgments
This project is part of a course or personal exploration in my continued journey in data science and, specifically, unsupervised machine learning.
Feel free to contribute, report issues, or suggest improvements!