A guide to upscaling images with AI

In this guide we’ll cover the many different ways you can upscale images with AI. We’ll cover the pros and cons of each approach, and how to choose the best one for your use case.

Upscaling increases an image’s resolution. AI is used to enhance the image by adding detail and fixing artifacts.

Imagine you have a small, somewhat blurry photo, and you want to make it larger and clearer, like turning a wallet-sized photo into a poster without losing quality. Traditional methods might make the photo bigger, but it would become even blurrier. AI upscaling models work a lot like a smart artist who not only enlarges the photo but also cleverly adds in details to make the larger photo look sharp and clear.

There is also a big overlap between image upscaling and image restoration. AI models for image restoration fix blemishes, remove noise and add detail, which is well suited to the upscaling process.

These are fast and cheap to run upscalers that work extremely well for low quality and badly compressed images. They can also fix faces, including distorted AI faces.

Many recent upscalers use diffusion based image generation as a way of hallucinating details and giving higher quality results. These run slower and so are more expensive, but they can go very large and produce magnificent images.