Image Super-Resolution Using a Wavelet-based Generative Adversarial Network

Understand

In this paper, we consider the problem of super-resolution recons-truction.

• This is a hot topic because super-resolution reconstruction has a wide range of applications in the medical field, remote sensing monitoring, and criminal investigation.
• Compared with traditional algorithms, the current super-resolution reconstruction algorithm based on deep learning greatly improves the clarity of reconstructed pictures.
• Existing work like Super-Resolution Using a Generative Adversarial Network (SRGAN) can effectively restore the texture details of the image.