Image Upscaler
Enlarge images 2x / 3x / 4x or to a custom size. Runs entirely in your browser.
Related Tools
What is image upscaling?
Upscaling increases an image’s pixel dimensions — making a 500×500 image into 2000×2000, for instance. Two main approaches exist: traditional interpolation (this tool, instant, no AI) which mathematically resamples existing pixels, and AI super-resolution(Real-ESRGAN, ESRGAN, GFPGAN) which uses neural networks to “hallucinate” detail that wasn’t there.
This tool uses Lanczos resampling, the same algorithm Photoshop’s “Image Size” dialog uses with “Bicubic Sharper” or “Preserve Details” settings. It produces clean, predictable enlargement — ideal when the source is already detailed and you just need more pixels for printing or larger display.
When this tool is the right choice
- You have a high-quality source that needs slightly larger dimensions (1.5× to 4×) — print, large display
- You don’t want artistic interpretation — AI can change faces, add textures that weren’t there, “improve” wrinkles in unwanted ways
- You need predictable output — same input always produces the same enlargement
- Privacy matters — runs locally, no uploads to AI services
- Speed matters — instant vs minutes for AI
When AI upscaling is better
- Severely undersized sources (200×200 → 2000×2000) — pure interpolation produces blurry results; AI can fill in plausible detail
- Old / scanned photos — AI face restoration tools (GFPGAN) recover faces from low-res scans
- Anime / cartoon — Real-ESRGAN-anime model is exceptional at vector-like artwork
- You’re OK with creative interpretation — AI may invent textures, smooth skin, etc.
Recommended AI tools (server-side, paid or free): Topaz Gigapixel AI, Replicate’s Real-ESRGAN, Upscayl (free desktop app), Adobe Super Resolution (in Camera Raw).
Output format
The tool preserves the input format (JPG → JPG, PNG → PNG, WebP → WebP). For photos, JPG/WebP. For screenshots and graphics with hard edges, PNG. To convert format afterward, use the corresponding converter tool.
What Upscaling Can and Cannot Do
Enlarging an image means creating pixels that were never captured. No algorithm can recover detail that the camera did not record — a blurry photo enlarged four times is a larger blurry photo.
What good upscaling does is make the invented pixels as plausible as possible. Simple methods average neighbouring pixels, which is why naive enlargement looks soft and washed out. Better resampling preserves edge contrast and gradient direction, so lines stay lines and text stays legible rather than dissolving.
The practical result: upscaling is excellent for logos, illustrations, and graphics with clean shapes, good for moderate enlargement of sharp photographs, and disappointing for small, noisy, or already-compressed images.
Getting the Best Result
Start from the largest original. Upscaling a thumbnail when a full-size version exists somewhere is wasted effort.
Avoid enlarging JPEG artefacts. Compression blocks and haloes get enlarged along with everything else, and become far more visible. A cleaner source at the same size beats a larger damaged one.
Do not chain enlargements. Going 2× then 2× again is worse than going 4× once, because the second pass amplifies the first pass’s guesses.
Consider whether you need raster at all. If the image is a logo and a vector version exists, exporting the SVG at the target size gives a genuinely perfect result rather than a plausible one.
FAQ
Does this apply any effect or filter?
No. It just makes the image bigger — the same way Photoshop’s Image Size dialog does with Lanczos resampling. No AI, no filter, no “enhancement”. The original look is preserved.
Will my image leave my device?
No. Everything runs in your browser via the Canvas API. Open DevTools → Network while you upscale and you’ll see zero outbound file uploads.
Why is the output capped at 6000 × 6000?
Browser canvases use about 4 bytes per pixel of RAM (so 6000×6000 = ~144 MB). Above this, mobile browsers (especially iOS Safari) crash the tab. The cap is a safety limit. For larger output, use desktop tools.
Can it add detail that wasn’t in the source?
No. AI upscalers can hallucinate detail; this tool only enlarges what’s already there. A blurry 200×200 image stays blurry, just with more pixels. For severely small sources, use an AI upscaler instead.
What’s the maximum scale factor?
2×, 3×, or 4× preset, or custom size up to 6000 × 6000. Anything beyond 4× from a small source produces visibly soft results — at that point, AI upscaling delivers better visual quality.
Can I batch upscale many images?
Currently single-image only. For batch processing, use ImageMagick command-line: magick input.jpg -filter Lanczos -resize 200% output.jpg.
Will upscaling make a blurry photo sharp?
No. The detail was never recorded, so it cannot be recovered. Upscaling makes the enlargement look as clean as possible; it does not add information.
Is 2x or 4x better?
Use the smallest enlargement that meets your requirement. Every additional factor multiplies the amount of invented content, and the result gets less convincing.
Should I upscale before or after compressing?
Before. Enlarging an already-compressed image magnifies its artefacts, which is the fastest way to a poor result.
What works best?
Logos, icons, illustrations, and clean line art, where edges are well defined. Small, noisy, or heavily compressed photographs are the hardest case.
⚠️ Reference Only
Output is generated based on your input and is provided for reference. Results may vary depending on your specific use case, edge cases, or environment-specific behavior. We do not guarantee accuracy of conversions, validations, or computed values.
Always verify critical outputs against official documentation or production environments. We are not responsible for any decisions or losses based on these tool results.