Upscale a Photo Without Losing Quality Using AI

Why AI upscaling beats simple resizing

When you enlarge an image the traditional way, the software just stretches the existing pixels and fills in blended colors: the result is blurry or pixelated, because no detail is added. A super-resolution AI like Swin2SR has learned from many images what edges, textures and sharp outlines look like. So it rebuilds plausible detail at the new size. In practice, a 500 × 500 pixel photo becomes a 1,000 × 1,000 pixel image at ×2, or 2,000 × 2,000 pixels at ×4, which is 16 times more pixels, with cleaner edges than a traditional stretch.

Which mode to choose: "Real photo" or "Fast"?

"Real photo" mode upscales ×4 and, at the same time, denoises the image and removes JPEG compression artifacts: blocks, halos around edges, bleeding colors. It's the right choice for an old photo saved from social media, an image sent through a messaging app or downloaded in low quality. "Fast" mode upscales ×2: it needs less computing power and works well when the image is already clean and you just need to double its size. Processing happens on your device: it's faster on a recent computer than on an old phone. Save as PNG to keep full quality, or as JPG for a smaller file; to fine-tune the exact dimensions afterward, use "Resize Image".

What AI upscaling can and can't do

AI invents plausible detail: it doesn't recover information that's truly lost. A slightly small or over-compressed photo gets noticeably sharper, but a very blurry, shaky or tiny photo won't magically become sharp. Text that's unreadable in the original won't become readable, and a blurry license plate won't be revealed. The tool doesn't rebuild faces or colorize black-and-white photos: it enlarges and cleans up the image as it is. For the best results, always start from the largest, least compressed file you have, rather than a screenshot of the photo.