Papers › Distortion-aware super-resolution for planetary exploration images
Distortion-aware super-resolution for planetary exploration images
Nicola Landro, Ignazio Gallo, Filippo Pelosi, Riccardo La Grassa, Anwar Ur Rehman
Super-resolution is crucial in computer vision and digital image processing, aiming to enhance low-quality images’ resolution and visual quality. This paper focuses on correcting the distortion introduced by fisheye lenses and improving the resolution of images for better detail representation. Specifically, we propose an evaluation approach that benchmarks three state-of-the-art models in different categories: Real-ESRGAN (convolutions), SwinIR (transformers), and SR3 (diffusion). We evaluate their performance in super-resolution and distortion correction tasks using metrics such as PSNR and SSIM. To facilitate this evaluation, we create and release a new dataset of lunar surface images with fisheye distortion applied. Our experiments demonstrate the effectiveness of each model in handling distortion and improving image resolution. The results show that large models generally outperform medium models, and PSNR models achieve higher PSNR and SSIM scores than GAN models. Additionally, we evaluate the distortion correction by comparing the corrected images with ground truth. Our findings contribute to understanding different model categories and their performance in super-resolution and distortion correction tasks. The proposed dataset and evaluation approach can be valuable resources for future research.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections