This does not add any detail to the image, it just smoothes out the transition between pixels.Ī neural network analyzes thousands of photo pairs to learn how details usually get lost. Interpolation algorithms work by approximating new pixels from the colors of surrounding ones. engine uses your computer’s graphics card to process your images quickly. Those photos were then used to create a sophisticated neural network that gradually learned the best way to enlarge, enhance, and create natural details. To teach the difference between low and high quality results, we started by gathering millions of photos of all subjects and styles.
Gigapixel’s new approach based on machine learning is a giant leap ahead: state-of-the-art “deep learning” methods allow it to enlarge images while actually adding new details. Interpolation-based photo enlargement software has been around for decades. Image enlargement: interpolation vs machine learning If you ever need to upscale your photo while preserving beautiful detail, take advantage of the most modern technology in the space and give Gigapixel AI a try. The highest-quality image upscaling that you can get anywhereīecause of these exceptional results, Gigapixel AI is used by everyone from leading photographers, to video game modders, to major motion studios. Then, it naturally accentuates and recovers detail while suppressing noise in your upscaled photo. Gigapixel AI successfully determines which image features are stars (detail) and what’s noise. It’s hard to believe that the crisp output image above was enlarged 4x, but it was. This is only possible through training and exposure to millions of test images.Ĭrisp photos that look like they were never upscaled
Gigapixel is different: it increases the actual sharpness of your upscaled photo by recovering real detail in your image. Increasing edge contrast is the simplest way to make an image look “sharp”, and how most other upscaling software works. Recover real details for actual sharpness
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