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Introduction to Super Resolution from an Expert

There are three major groups studying image super-resolution in the world.

The super-resolution is quite close to the image restoration/deconvolution. So, it’ll be helpful to check such relevant papers. The above three groups has published many papers, but heuristics are often included in their papers. I guess it is better to know a rather simple basic theoretical foundation.

From that point, I will recommend to see Bishop’s paper at first. Bishop is a pioneer of the super-resolution from Bayesian stand point: Bayesian image super-resolution Tipping, M. E., & Bishop, C. M. (2003). is a paper presented at NIPS.

We (people in Ishii Lab)  also invented a Bayesian super-resolution by incorporating line process originally invented by Geman & Geman. Superresolution with compound Markov random fields via variational EM algorithm

For a practical use, it is important to process quickly. Okutomi’s lab has invented good algorithms that can be used in practice. Actually, they sell their system for commercial use now. Their papers are worth reading.

Source: Dr. Shin-ichi Maeda


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