In this project we apply Gibbs Sampling based on different Markov Random Fields (MRF) structures to solve the image denoising problem. Compared with methods like gradient ascent, one important advantage that Gibbs Sampling has is that it provides balances between exploration and exploitation. This project also discusses about the behaviours of different MRF structures.
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