Upscale an image's resolution in pixels
Resizes by interpolation to a scale or an exact dimension — no AI, and no inventing detail the original image doesn't have.
Drag one or more images here, or click to choose
JPG, PNG, or WebP, up to 25 MB each
This tool increases the image's pixel count — it doesn't recover detail that doesn't exist in the original file. A small, blurry photo stays blurry, just bigger. It's meant for hitting a minimum dimension a system requires, prepping an image for printing at a larger size, or standardizing the dimensions of a set of images.
Result
The result appears here after upscaling the image.
Just need to shrink the file size in KB, without changing the dimension? Use reduce image size. If the final ratio needs to be different from the original, crop the image first with crop image.
Local processing: your file never leaves your computer.
- Does:Resizes by interpolation to a scale or an exact dimension — no AI, and no inventing detail the original image doesn't have.
- Processes:Your image is processed entirely in your browser — nothing is uploaded to a server.
- Doesn't do:The resize runs in multiple steps of up to 2x each, to preserve more sharpness than a single jump — even so, the result never has more real detail than the original image.
What this tool actually does
This tool increases an image's pixel count through interpolation — a resampling technique that calculates each new pixel from the neighboring pixels already present in the original image. There's no AI here, no model running behind the scenes, and no attempt to guess what "should" be in an area of the photo. The result has more pixels, but not more information than the input file already contained.
That matters because there's a common expectation, shaped by a different category of tool, that "increasing resolution" makes a photo sharper or recovers lost detail. That's not what happens here, and this distinction is the central point of this page, not a footnote: if the image you upload is blurry, pixelated, or low on detail, the result is a larger version of that same image, with the same blur, pixelation, or lack of detail — just spread over a bigger area.
So what's it actually for
There are legitimate uses for increasing dimensions without adding detail. The most common is meeting a minimum size requirement: sign-up systems, listing forms, and marketplace catalogs often reject images below a specific width or height in pixels, even when the image's visual quality is already good enough for the intended use. Increasing the dimension clears that kind of administrative blocker.
Another use is prepping an image for printing at a physical size larger than the original file was meant to support — a photo captured for a screen may need more pixels to fill a sheet of paper without getting visibly stretched by the printing software itself. And the third use is standardization: when a set of images of different sizes needs to end up at the same dimension before being published, resizing everything to a common value handles that in one batch pass.
Scale or exact dimension
The tool offers two ways to set the final size. By scale, you choose 2x, 3x, or 4x, and the original image is multiplied equally on both dimensions — the ratio never changes in this mode. By exact dimension, you type the width in pixels (and, with "keep aspect ratio" checked, the height is calculated automatically from it, without distorting the image).
Unchecking "keep aspect ratio," width and height apply exactly as typed, even if that stretches the image — a deliberate option for the rare cases where a system requires a specific ratio that isn't the original image's. For most uses, that's not what you want: if you need a different ratio without stretching anything, the right move is to crop the image to the desired ratio first, then upscale afterward.
Dimension presets
Below the width and height fields there are shortcuts for a few common widths: 1000 px (a typical minimum on marketplaces and catalogs), 1080 px (the standard square post size on social media), 1500 px (a common requirement for ads or e-commerce listings), and 2480 px (the width of a portrait letter-size sheet at 300 DPI, for printing). Clicking a preset fills in the width with that value and keeps the original ratio — the final height depends on your image's ratio, it isn't locked to the preset's value.
Why the resize happens in steps
Upscaling an image in a single very large jump — going straight from 1x to 4x, say — produces a noticeably softer result than the same final enlargement done in two or three smaller stages, each up to 2x, even using the same best-quality resampling available in the browser both times. So whenever the requested enlargement goes above 2x, the tool automatically splits the work into those smaller stages before reaching the final size — with no extra configuration on your part.
Batch mode with the same setting
When more than one image is uploaded at once, the same scale or dimension setting applies to all of them, processed one at a time. If any image in the batch is already equal to or larger than the target size, it's flagged as such in the result and left unchanged — this tool increases resolution, it never reduces it, even if the chosen setting would have resulted in that for a specific file in the queue.
What this tool doesn't do
It doesn't recover lost detail, doesn't remove blur, doesn't use AI, and doesn't change the image's content beyond its pixel count — no cropping, no added elements, no color adjustments. If the goal is to shrink a file's size in KB, the "Reduce image size" tool (linked below the result on this page) handles that. If the goal is to change the visible area or the ratio of the image before upscaling, the "Crop image" tool does that cropping first.
Frequently asked questions
Why is my photo still blurry after upscaling it?
Because the tool redistributes the pixels that already exist across a larger image — it doesn't invent detail that wasn't captured in the original file. If the source photo is small and blurry, the result is a bigger version of that same blurry photo, just with more pixels. AI super-resolution tools try to predict detail that isn't in the file; this tool doesn't do that — it only resizes.
Is increasing an image's dimensions the same as it getting higher quality?
No. Dimension is the pixel count (width × height); quality has to do with sharpness, noise, and real detail captured at the moment the photo was taken. This tool only changes the first thing. A sharp image at 500×500 px stays sharp at 1500×1500 px; a blurry image at 500×500 px stays blurry at 1500×1500 px — just bigger.
What's the point of upscaling if it doesn't add detail?
For three common situations: meeting a minimum dimension requirement from a sign-up system, upload form, or listing that rejects small images; prepping an image for printing at a size larger than the original file handles well; and standardizing the dimensions of a set of images before publishing. In none of these cases is the goal to make the image look sharper — it's to give it the required pixel count.
What's the difference between scale and an exact pixel dimension?
By scale (2x, 3x, 4x), the original image is multiplied on both dimensions, always keeping the ratio. By exact dimension, you type the width (and, optionally, the height) in pixels — with "keep aspect ratio" checked, the height is calculated automatically from the width; unchecked, both dimensions apply exactly as typed, which stretches the image if they don't match the original ratio.
Why is the resize done in several steps instead of one?
Upscaling in a single very large jump (say, straight from 1x to 4x) produces a visibly softer result than the same enlargement done in two or three stages of up to 2x each, even using the best resampling available in the browser both times. That's why the tool always splits large enlargements into multiple steps — automatically, with no extra configuration needed.
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