The short answer
Sharpening increases local edge contrast, deblurring tries to estimate the original shape hidden by blur, and upscaling creates a larger image. These are different tasks. A sharper image is not automatically a higher-resolution image, and a 2x AI result may contain model-estimated detail rather than recovered fact.
The three methods
| Method | Best for | What to expect | What it cannot promise |
|---|---|---|---|
| Local sharpening | Slightly soft edges, scans, simple graphics | More visible edge contrast with no upload in Local mode | It cannot reconstruct severe motion blur |
| Deblurring | Motion blur or missed focus | A model may estimate a cleaner edge structure | There is no guaranteed recovery of missing detail |
| Super-resolution/upscaling | Small images that need a larger output | A 2x image with estimated fine detail | It does not prove that every invented texture was in the source |
A reliable workflow
1. Inspect the source at 100 percent
Look at a face, a line of text, a high-contrast edge, and a textured area. Decide whether the problem is softness, noise, size, or real blur. Save the original before processing.
2. Try Local Sharpen first for a mild problem
Choose Local Sharpen when privacy and a quick result matter. Adjust strength and light denoise together. Too much strength creates bright or dark halos; too much denoise removes small texture. Stop when the edge is easier to read but still looks natural.
3. Use AI 2x only for a real size need
Choose AI 2x Enhance when you need a larger WebP output. The site prepares a resized copy in the browser and uploads it only after you run the AI job. High Quality is intended for finer detail; Fast is intended for a quicker result. A cold cloud worker can take longer, and the result can contain estimated detail.
The current AI path accepts JPEG, PNG, and WebP. The upload copy is reduced to the documented processing limits; very complex images may need Local mode instead.
4. Compare before downloading
Use the before/after slider. Check text, repeated patterns, hair, skin, and straight lines. If a logo changes shape or a texture becomes a repeated pattern, treat that output as an enhancement preview, not an authoritative restoration.
Example: a small product photo
For a 640 x 480 product image used in a draft catalogue, Local Sharpen may be enough if the dimensions are acceptable. If the catalogue requires twice the pixel dimensions, run AI 2x and inspect the label at 100 percent. Keep the original and compare both files in the final layout.
What not to claim
Do not describe a sharpened image as forensic evidence. Do not call every blurred photo recoverable. Do not promise face restoration unless a tested, explicitly supported face-restoration model is actually available. Honest limits improve the decision a reader makes after the article.
Troubleshooting
- Local processing fails: try a supported JPEG, PNG, or WebP file and reduce the image size if the browser runs out of memory.
- AI upload is rejected: the source may exceed the AI pixel or byte limit; use Local mode or prepare a smaller copy.
- The job takes too long: cancel it once rather than submitting the same image repeatedly. A timeout should not be treated as a successful result.
- The result looks artificial: reduce sharpening, compare at 100 percent, and keep the original as the fallback.
Sources
Model-assisted super-resolution reference: Real-ESRGAN project. Image format reference: MDN image formats. Mode names, limits, privacy behavior, and output claims must match the live tool implementation.
Tool link: https://www.aisharpenimage.net/
Suggested visual: a self-created test sheet containing text, a straight edge, and a textured object, shown before and after with the tool's comparison slider.