What Is AI Upscaling?
Traditional image resizing (bicubic, bilinear) simply stretches pixels, resulting in blurry, soft images. AI upscaling uses machine learning to intelligently add detail as it increases resolution. The result is a larger image that looks sharp and natural, not stretched.
AI Upscaling in QuickRemove
QuickRemove includes AI upscaling that can increase your image resolution by up to 4x. This is available on paid tiers:
- Basic tier — Fast upscale mode
- Pro tier — Fast + Quality upscale modes
The Fast mode prioritizes speed while still producing good results. The Quality mode (Pro only) takes more time but produces the best possible output.
How to Upscale an Image
1Open Your Image
Drop your image into QuickRemove. You can upscale with or without background removal — both workflows are supported.
2Select Upscale Option
Choose the AI upscale option and select your desired scale factor (up to 4x).
3Choose Mode
Select Fast (available on Basic and Pro) or Quality (Pro only) mode depending on your needs.
4Process and Export
The AI processes the image and produces a higher-resolution version. GPU acceleration significantly speeds up this process.
When to Use AI Upscaling
- Small product photos — scale up images that are too small for marketplace requirements (e.g., Amazon's 1000px minimum)
- Old or low-res images — improve older photos that were captured at lower resolutions
- Print preparation — make screen-resolution images large enough for high-quality prints
- Cropped images — after heavy cropping, use upscaling to restore usable resolution
Upscale + Background Removal
A powerful workflow is combining both features: remove the background from a small image, then upscale the result. This is useful when you have low-resolution product photos or screenshots that need both a clean background and higher resolution for professional use.
Hardware Considerations
AI upscaling is computationally intensive. A compatible GPU (NVIDIA, AMD, or Intel) will process images much faster than CPU alone. For 4x upscaling of large images, a GPU is strongly recommended.