Sekundarni povzetek: |
Due to the increasing resolution of displays, the use of algorithms for super-resolution has become significantly more common. By employing these algorithms, faster image rendering can be achieved. Additionally, super-resolution algorithms enable the upscaling of images from lower to higher resolutions. These algorithms can operate on a single image or multiple images. Today, neural networks are predominantly used for this purpose. As new algorithms for super-resolution have emerged in 3D graphics, and there is limited performance data about them, I conducted an analysis and compared them. I obtained images for analysis using Unity. For the analysis, I employed the following methods: PSNR, SSIM, MSE and BRISQUE. To examine details, I calculated difference images using the baseline reference full resolution image. For each individual algorithm, I described its functioning, strengths, and weaknesses. In conclusion, I compared the results among the various algorithms and attempted to categorize them. |