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Image Resizer, Resize Photos Online

Resize images by width, height or percentage, lock the aspect ratio and pick a fit mode. 100% in your browser, no uploads.

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Frequently asked questions

Are my images uploaded to any server?
No. Resizing is done entirely within your browser using the HTML Canvas API. The image data is loaded into local memory and the resized version is generated there. Nothing is sent over the network, making this tool safe for private or confidential photos.
What is aspect ratio and why should I lock it?
The aspect ratio is the proportional relationship between an image's width and height — for example 16:9 or 4:3. Locking the aspect ratio ensures that when you change one dimension, the other adjusts automatically so the image is not stretched or squashed. Unlocking it lets you force any dimensions you need, but the result may look distorted.
What is the difference between Contain, Cover and Stretch fit modes?
Contain scales the image so it fits entirely inside the target dimensions while preserving the aspect ratio; the canvas may have empty space on two sides. Cover scales and crops the image so it fills the entire target box with no empty space, cropping the overflow from the centre. Stretch ignores the aspect ratio entirely and forces the image into exactly the specified width and height.
Can I resize an image by percentage instead of fixed pixels?
Yes. Selecting the percentage mode lets you type a value such as 50 % to halve both dimensions, or 150 % to scale up. The tool computes the resulting pixel dimensions automatically. This is useful when you want to quickly downscale a batch of images by a consistent factor.
What formats are supported as input and output?
The tool accepts JPG, PNG, and WebP images as input. The output can be saved as any of those three formats. Converting from PNG to WebP during a resize is a common workflow because it reduces file size while also adjusting the dimensions in a single step.
Is there a maximum resolution or file size?
There is no enforced limit, but browsers impose an internal maximum canvas size — typically around 16,384 × 16,384 pixels. Images exceeding that will fail to render. Very large files (above 20 MB) may also be slow to process. If you encounter issues, consider splitting the task or using a desktop application.
Why should I serve multiple image sizes on a website?
The HTML srcset attribute lets browsers download only the image size appropriate for the current viewport and device pixel ratio, avoiding unnecessary data transfer. A visitor on a 375 px wide mobile screen has no need to download a 2400 px wide image. Serving correctly sized images is one of the most impactful recommendations in Google's Lighthouse performance tool and contributes directly to better Core Web Vitals scores.
Does resizing affect image quality?
Downscaling (making an image smaller) generally has little visible impact because pixels are merged and averaged. Upscaling (making an image larger) always involves inventing pixel data that was not in the original and results in a blurry or pixelated appearance. The Canvas API uses bilinear interpolation by default, which produces smooth upscales but cannot recover lost detail.
What does megapixel mean and why does it matter?
A megapixel is one million pixels. A 12-megapixel camera produces images roughly 4000 × 3000 pixels in size. Megapixel count matters because it directly determines file size, processing time, and how large you can print an image before it looks pixelated. For web use, images rarely need to exceed 2–3 megapixels, so resizing a 12 MP phone photo before uploading it to a website saves significant bandwidth and storage.
How does browser-side resizing compare to Photoshop or other desktop tools?
Professional tools like Photoshop offer advanced interpolation algorithms (Bicubic Sharper for downscaling, Bicubic Smoother for upscaling) that can produce marginally better results than the browser's bilinear interpolation, especially at extreme scale factors. For typical web and social media use cases — resizing photographs by less than a factor of four — the Canvas API output is visually indistinguishable from desktop tools.

About Image Resizer, Resize Photos Online

Resizing an image means changing the number of pixels that make up its width and height, which in turn affects both the file size and how the image displays on screen. A digital image's resolution is measured in megapixels — a 4000 × 3000 image contains 12 million pixels. Halving both dimensions to 2000 × 1500 reduces the pixel count to 3 million, cutting the raw data by 75 %. Understanding the difference between an image's intrinsic pixel dimensions and the CSS size at which a browser renders it is essential for web performance: an image that is 4000 px wide but displayed in a 400 px container forces the browser to download ten times more data than necessary.

Web developers, graphic designers, social media managers, and bloggers all resize images daily. A responsive web design typically requires the same photograph at three or four different widths — a full-resolution original for large monitors, a medium variant for tablets, and a compact thumbnail for mobile — served via the HTML srcset attribute so browsers download only the size they need. E-commerce platforms need consistent thumbnail dimensions for product grids. Email marketers must keep images below strict size caps. Print workflows require specific DPI and millimetre targets. The single act of resizing to the right dimensions before upload can save gigabytes of storage and dramatically speed up page loads.

This tool performs every resize operation locally in your browser using the HTML Canvas API, so your images never leave your device. You can specify an exact target width, an exact height, or a percentage of the original dimensions. Enabling the aspect-ratio lock ensures the image is never stretched or squashed. Three fit modes give you fine-grained control: Contain scales the image to fit entirely inside the target box (the canvas is padded if necessary), Cover fills the box and crops the overflow from the edges, and Stretch forces the image into the exact dimensions regardless of proportion. The result is available as a PNG, JPEG, or WebP download at whatever quality you choose.

A few tips for best results: always lock the aspect ratio unless you specifically need a distorted output. When generating thumbnails for a website, aim for the exact display size rather than relying on CSS to scale down — serving correctly sized images is one of the quickest wins in a Lighthouse performance audit. If you need to produce multiple sizes of the same image, resize to the largest first, then resize that output down to the smaller sizes, as this preserves more detail than repeatedly downscaling from the original. For retina and high-DPI displays, produce images at 2× the CSS display size to ensure crisp rendering.

Pixels, Megapixels, and the Long Road to Responsive Images

The word "pixel" is a portmanteau of "picture element" and was coined in the late 1960s by engineers at NASA's Jet Propulsion Laboratory who needed a term to describe the individual cells of digitised images returned by space probes. The first consumer digital camera capable of capturing a full megapixel was the Kodak DCS 100, released in 1991 at a price of around $13,000 — it stored images on a separate hard-drive unit worn on a shoulder strap. By 2010, budget smartphones were shipping with 5-megapixel cameras, and by 2023, flagship phones routinely exceeded 200 megapixels, creating a paradox where the cameras in our pockets produce images far larger than any screen can display.

The concept of responsive images — serving different image sizes to different devices — predates the modern web by decades. Early television broadcast engineers faced an analogous problem when designing systems that had to work on screens ranging from tiny portable sets to large living-room consoles. On the web, the problem became acute around 2010 when Apple introduced the Retina display, which doubled the pixel density of the iPhone 4 screen. Developers suddenly had to serve images at twice the resolution for these devices or accept blurry photos, while not penalising regular-screen users with unnecessarily large downloads. This tension drove the creation of the HTML srcset attribute, standardised in 2014, and the picture element, both of which allow browsers to select the most appropriate image size automatically.

Before digital zoom existed, optical zoom in cameras was achieved by physically moving lens elements — the same principle that telescope makers had used since the 17th century. Digital resizing algorithms, by contrast, are a product of signal-processing mathematics developed in the 20th century. The bilinear interpolation method used by most browsers today was described in a 1975 paper, while bicubic interpolation — favoured by professional image editors — was introduced by Robert Keys in 1981. Modern AI-based upscaling tools use convolutional neural networks trained on millions of image pairs to "invent" plausible detail when enlarging images, producing results that older mathematical methods simply cannot match.

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