Image Restoration Using Conditional Random Fields and Scale Mixtures of Gaussians

Understand

This paper proposes a general framework for internal patch-based image restoration based on Conditional Random Fields (CRF).

• Unlike related models based on Markov Random Fields (MRF), our approach explicitly formulates the posterior distribution for the entire image.
• The potential functions are taken as proportional to the product of a likelihood and prior for each patch.
• By assuming identical parameters for similar patches, our approach can be classified as a model-based non-local method.