Statistical models, on the other hand, aim to capture the variability and dependencies in the data via joint or conditional PDFs. Specifically, they treat image data as realizations of random fields. A prominent example of such models is the MRF model [99] that we discussed in Section 2.6. Such models are good at capturing the regularities in natural images that are rich in texture-like features.