Learning Parametric Distributions for Image Super-Resolution: Where Patch Matching Meets Sparse Coding

ICCV 2015 Yongbo LiWeisheng DongGuangming ShiXuemei Xie

Existing approaches toward Image super-resolution (SR) is often either data-driven (e.g., based on internet-scale matching and web image retrieval) or model-based (e.g., formulated as an Maximizing a Posterior estimation problem). The former is conceptually simple yet heuristic; while the latter is constrained by the fundamental limit of frequency aliasing... (read more)

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