/Image-Restoration-with-Gibbs-sampler

Reconstructing a black and white Japanese woodblock print using Bayesian inference

Primary LanguageJupyter Notebook

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!