Deep Burst Super-Resolution

Understand

While single-image super-resolution (SISR) has attracted substantial interest in recent years, the proposed approaches are limited to learning image priors in order to add high frequency details.

• In contrast, multi-frame super-resolution (MFSR) offers the possibility of reconstructing rich details by combining signal information from multiple shifted images.
• This key advantage, along with the increasing popularity of burst photography, have made MFSR an important problem for real-world applications.
• We propose a novel architecture for the burst super-resolution task.