StarryFrameOld product photo restoration for legacy ecommerce catalogs
Old product photo restoration for legacy ecommerce catalogs
Many stores still rely on old product photos that were exported too small or compressed years ago. This page focuses on improving those legacy assets before replacing an entire catalog shoot.
When restoring old product photos is worth trying
- A legacy catalog still sells, but the image quality no longer fits the current storefront design.
- Older supplier photos are usable but visibly undersized or soft on zoom.
- You need an interim quality improvement before scheduling new photography.
What AI can and cannot fix
- It can often improve resolution, edge clarity, and compression artifacts on usable old images.
- It cannot fully recover severe blur, incorrect lighting, or missing scene information in every case.
- The safest workflow is to process a sample set and compare before replacing your published assets.
How to operationalize it
- Start with the highest-traffic or highest-margin SKUs and review output manually.
- Use batch jobs when many old files share the same source quality limitations.
- Move to the API if restoration needs to happen as part of a broader catalog migration.
FAQ
Can AI restore old product photos?
It can often improve old product photos when they are still usable but too small, soft, or compressed. Severely damaged files may still require manual work or reshooting.
Is this better than re-photographing products?
A reshoot is often best for top SKUs, but AI restoration can be a practical bridge for large legacy catalogs where replacing every image immediately is unrealistic.