PSNR Calculation MATLAB Code for PIRM-SR Challenge

The PIRM-SR challenge aims to compare and rank perceptual single-image super-resolution methods. In terms of perceptual quality, state-of-the-art methods often perform poorly when evaluated with 'simple' distortion metrics like PSNR and SSIM. Hence, in contrast to previous challenges, the evaluation and ranking will focus on perceptual quality, adopting a unified approach that combines algorithm accuracy with perceptual quality. This allows perceptual-driven methods to compete with those designed to maximize PSNR.

To self-verify your method, use this MATLAB code to compute RMSE and perceptual scores for your output on a self-validation set. Here's how to quickly get started:

  1. Copy your output to the your_results folder in the base directory.
  2. Copy only the HR images to the self_validation_HR folder.
  3. Download and extract the SR-Metric toolbox into the utils/sr-metric-master folder.
  4. Run the evaluate_results.m script.

Troubleshooting

Depending on your operating system, you might need to recompile the MEX files in the matlabPyrTools toolbox. If that's the case, follow these steps:

- Navigate to utils/sr-metric-master/external/matlabPyrTo and recompile the MEX files.