AI Photo Restoration for Old and Damaged Photos

Often, yes! Artificial intelligence photo restoration reconstructs what belongs in a torn area by reading the image around it. Backgrounds and clothing recover especially well. Heavily damaged faces remain the hardest case.

Pixelcut works from what survives in your scan rather than inventing features. Where damage covers part of a face the reconstruction is an estimate. Check the result against another photo.

Scratches, tears, creases, dust spots, stains, and faded or yellowed tones. A restoration photo run detects whatever is in your scan. If a photo is undamaged and only small, use the image upscaler.

Yes! Photo restoration rebuilds detail as it repairs the damage. Your file comes back around two and a half times the original in each dimension, which is plenty for printing.

Yes! You can colorize photos in the same pass as restoration. An old monochrome print comes back repaired and in full color rather than needing two separate runs.

They are processed securely and are not shared. That matters especially for family heirlooms, where the scan you upload is often the only surviving copy of the original print.

Upload JPG, PNG, WebP, or HEIC. A flatbed scan gives the AI the most detail to work with, though a phone shot of the print works too, with no conversion needed.

Each photo gets its own run right now, which keeps old photo restoration targeted to the damage the restoration tool actually finds on that particular print rather than one generic pass.

Prints with damage around the edges recover most fully, since the surrounding image gives the AI plenty of context. Photos stored flat in albums usually beat loose prints, which pick up more surface wear.