Blind Image Super-Resolution: A Survey and Beyond

Understand

Blind image super-resolution (SR), aiming to super-resolve low-resolution images with unknown degradation, has attracted increasing attention due to its significance in promoting real-world applications.

• Many novel and effective solutions have been proposed recently, especially with the powerful deep learning techniques.
• Despite years of efforts, it still remains as a challenging research problem.
• This paper serves as a systematic review on recent progress in blind image SR, and proposes a taxonomy to categorize existing methods into three different classes according to their ways of degradation modelling and the data used for solving the SR model.