Summary Overview
Understanding effective resolution based on pixel size and print dimensions, and how Filecheck applies AI upscaling to fix blurry files.
What is Effective DPI?
Effective DPI is the actual resolution of an image when scaled to its final printed dimensions. It is calculated by dividing the pixel dimensions of the image by the physical printed dimensions in inches: $$\text{Effective DPI} = \frac{\text{Pixel Width}}{\text{Printed Width (inches)}}$$
For example, a $1500 \times 1500\text{ px}$ image printed as a $5 \times 5\text{ inch}$ card has an Effective DPI of 300. If scaled up to print as a $10 \times 10\text{ inch}$ sign, its Effective DPI drops to 150, making it blurry.
The Print Risk: Grainy and Blurry Images
End-users often upload web images (like Instagram photos or screenshots) expecting them to print clearly on large canvases.
- Pixelation: Small pixel counts stretched over large surfaces look blocky and unprofessional.
- Rejecting orders: Standard preflight systems reject low-DPI uploads, forcing store owners to manually request higher-resolution copies, delaying orders and decreasing checkout conversions.
How Filecheck Repairs Low DPI with AI Upscaling
Rather than rejecting a customer’s low-resolution image, Filecheck can automatically remediate it:
- DPI Verification: We measure the image’s pixel dimensions against the target print size configured for the product.
- AI Upscaling Autofix: If the effective resolution is below the minimum limit (e.g. 300 DPI), Filecheck runs the image through a serverless AI Upscaling (Super-Resolution) model.
- Enhancement: The AI fills in missing details, refines blurry edges, and interpolates pixels to increase resolution up to 4x.
- Instant Approval: The customer is shown a sharp, upscaled soft-proof instantly, allowing checkout to proceed without manual delay.