Resize images instantly in your browser — no uploads, fully private
Resizing images is one of the most common tasks in digital workflows, yet it has historically required installing heavyweight software or uploading sensitive files to a third-party server. Our Image Resizer solves both problems at once: it runs entirely inside your web browser using the HTML5 Canvas API, meaning your photos and graphics never leave your device. Whether you are preparing images for a social media post, optimising a website for faster loading, or scaling a batch of product photos to a uniform size, this tool gives you precise control without any downloads, registrations, or subscriptions. The tool supports three primary resize modes. Pixel mode lets you enter exact width and height values in pixels, with an optional aspect-ratio lock that automatically adjusts the second dimension when you change the first — so a 4000×3000 landscape photo stays proportional when you set the width to 1200 pixels. Percentage mode lets you scale an image up or down relative to its original size using a slider or quick-select buttons (25%, 50%, 75%, 150%, 200%), which is ideal when you want to halve a batch of images without thinking about exact pixel counts. Presets mode provides one-click dimensions for every major social media platform — Instagram posts, stories, and reels; Facebook posts and covers; Twitter/X headers; YouTube thumbnails and channel art; LinkedIn posts and banners; and Pinterest pins — as well as standard web and print sizes from 150×150 thumbnail up to 3840×2160 4K. Beyond simple stretching, the tool offers three fit modes that control what happens when your target dimensions do not match the original aspect ratio. Stretch fills the exact target box and may distort the image. Fit Within (letterbox/pillarbox) scales the image to fit entirely inside the target box while preserving its aspect ratio, then fills any remaining space with a solid background color of your choice — or a blurred version of the image itself for a more polished look. Fill & Crop scales the image so it completely covers the target box, then crops the edges symmetrically, which is perfect for social media formats that demand exact dimensions. For image quality, you can choose between JPEG, PNG, and WebP output formats. JPEG and WebP both support a quality slider from 1 to 100 (default 90) that trades file size against visual fidelity. PNG output is always lossless. If you have a strict file size budget — for example an email newsletter that must stay under 500 KB — you can enter a target file size and the tool will automatically binary-search the optimal quality setting to meet it. The resampling algorithm selector gives you three options: Lanczos (multi-step downscale that produces the sharpest results and is recommended for downscaling photos), Bicubic (balanced quality and speed), and Bilinear (fastest, suitable for simple tasks). Batch processing supports up to 20 images simultaneously. Each image is processed sequentially to avoid memory spikes, and you can download results individually or all at once. A CSV export gives you a full stats report — original and output dimensions, original and output file sizes in KB, and percentage reduction for each file — useful for documenting an optimisation project or comparing compression strategies.
Understanding Image Resizing
What Is Image Resizing?
Image resizing is the process of changing the pixel dimensions of a digital image — its width and height measured in pixels. When you resize an image smaller (downscale), the software must discard pixels and blend neighboring colors to produce a smaller representation. When you resize larger (upscale), new pixels are interpolated from the existing data. The quality of this process depends on the resampling algorithm used. Bilinear interpolation averages a 2×2 pixel neighborhood; bicubic uses a 4×4 neighborhood and produces smoother gradients; Lanczos uses a sinc-based kernel and generally produces the sharpest edges when downscaling. Modern browsers implement bilinear by default via the Canvas API, but you can simulate Lanczos-quality results by downscaling in multiple half-steps — a technique this tool employs automatically when you select the Lanczos algorithm option.
How Does the Canvas API Resize Images?
This tool uses the HTML5 Canvas API, which runs entirely in your browser without any server communication. When you upload an image, it is read into memory as an ImageBitmap object via FileReader and URL.createObjectURL(). A canvas element is then created at the target dimensions, and ctx.drawImage() renders the source image onto the canvas at the desired size and position. For JPEG and WebP output, canvas.toBlob(callback, mimeType, quality) encodes the canvas pixels to a compressed binary blob with a quality parameter between 0.0 and 1.0. For PNG, the quality parameter is ignored and the output is always lossless. The resulting blob is wrapped in an object URL (URL.createObjectURL) to create a preview and download link that points directly to in-memory data — no HTTP requests involved.
Why Image Optimization Matters
Images are typically the largest contributor to web page weight. According to HTTP Archive data, images account for roughly 50–60% of a typical webpage's total bytes transferred. A single unoptimized 4 MB DSLR photo on a product page could add 3–4 seconds of load time on a mobile connection, directly increasing bounce rates and reducing conversions. Google's Core Web Vitals (particularly Largest Contentful Paint) explicitly penalize slow image loading in search rankings. For social media, most platforms silently re-compress images you upload — if you submit a 5 MB JPEG, the platform might save it at a quality setting that introduces visible artifacts. Uploading an image that is already at the platform's ideal dimensions and quality prevents double-compression and preserves visual fidelity. For email campaigns, staying under size limits avoids images being blocked by corporate mail filters.
Limitations and Browser Constraints
While the Canvas API is powerful, it has a few limitations worth understanding. First, maximum canvas dimensions are browser-dependent — Chrome typically allows up to 16,384×16,384 pixels, but Safari's limit can be lower on older devices. Attempting to create a canvas larger than the limit silently fails with a blank output. Second, DPI (dots per inch) is a metadata value that describes physical print size but does not affect pixel count — canvas-generated images cannot embed DPI metadata without a library. The physical print size displayed in this tool (at your selected DPI) is informational only. Third, HEIC/HEIF images (from iPhones) are not natively supported by most desktop browsers; Safari on Mac and iOS is the primary exception. Fourth, very large batch jobs (20 images each over 10 MB) may cause memory pressure on low-end devices — process in smaller batches if you encounter browser slowdowns or crashes.
How to Use the Image Resizer
Upload Your Images
Drag and drop one or more images onto the upload area, or click it to open a file browser. You can upload up to 20 images at once. JPEG, PNG, WebP, and GIF formats are supported.
Choose Resize Settings
Select Pixels mode to enter exact dimensions, Percentage mode to scale proportionally, or Presets mode to choose a social media or web standard size. Use the aspect ratio lock to keep proportions correct automatically.
Set Format, Quality, and Fit Mode
Choose JPG, PNG, or WebP output format. Adjust the quality slider for JPG/WebP to balance file size and visual quality. Select Fit Within to add background padding, or Fill & Crop to center-crop to exact dimensions.
Resize and Download
Click Resize Images. Results appear immediately with a before/after file size comparison. Download individual images or use Download All for batch results. Export a CSV stats report or print a summary using the action buttons.
Frequently Asked Questions
Are my images uploaded to a server?
No. This tool is 100% client-side. All image processing happens inside your web browser using the HTML5 Canvas API. Your images are never transmitted to any server, stored anywhere, or accessible to anyone other than you. This makes it safe for sensitive or confidential photos. The only data that leaves your device is what you explicitly choose to download. You can even use the tool while offline after the page has initially loaded, since no server calls are made during processing.
What is the difference between Fit Within, Fill & Crop, and Stretch?
Fit Within (letterbox/pillarbox) scales your image so it fits completely inside the target dimensions while preserving its original aspect ratio. Empty space is filled with a solid background color or a blurred version of the image. Fill & Crop scales the image so it completely covers the target dimensions, then symmetrically crops the overflow from the edges — this is ideal for social media formats that require exact dimensions. Stretch ignores the original aspect ratio entirely and maps the image to exactly fill the target box, which can cause visible distortion for non-square targets.
Which resampling algorithm should I use?
For most photo downscaling tasks, choose Lanczos. It uses a multi-step halving approach that preserves fine details and produces the sharpest edges. Bicubic is a good balance of quality and speed and is widely used by professional image editors. Bilinear is the browser's native algorithm and is fastest, but can produce slightly softer results when scaling down significantly. For upscaling (making images larger), differences between algorithms are less noticeable at moderate scales. If you are enlarging an image more than 2×, the result will inevitably be softer regardless of algorithm because new pixel data must be invented.
Why does my PNG output sometimes have a larger file size than the original?
PNG uses lossless compression, which means it preserves every pixel exactly. If you resize a JPEG to a larger canvas size (upscale) and save as PNG, the output will be much larger because PNG stores every pixel without compression loss, while JPEG was heavily compressed in the original. Similarly, if you add letterbox padding (background bars) to a JPEG and save as PNG, the larger canvas has more pixels to store. To reduce PNG file size, try switching to WebP output at high quality — WebP supports both lossless and lossy modes and typically produces 25–34% smaller files than PNG at equivalent quality.
How does the Target File Size feature work?
When you enter a target file size in KB and click Resize, the tool draws the image onto a canvas at your specified pixel dimensions, then performs a binary search over the quality parameter (0–100) to find the highest quality setting that produces a file at or below your target size. It runs up to 12 iterations to converge on the optimal quality value. This feature only works with JPEG and WebP output formats — PNG is always lossless and cannot be constrained to a specific file size by adjusting quality. Note that the final file size depends on image content; highly detailed images compress less than simple flat-color images at the same quality setting.
What are the best image dimensions for social media platforms?
Recommended dimensions as of 2025: Instagram square post 1080×1080px, portrait post 1080×1350px, story/reel 1080×1920px. Facebook post image 1200×630px, cover photo 820×312px. Twitter/X post 1600×900px, header 1500×500px. YouTube thumbnail 1280×720px (16:9), channel art 2560×1440px. LinkedIn post 1200×627px, company cover 1584×396px. Pinterest pin 1000×1500px (2:3 ratio). All major platforms re-compress uploaded images, so always upload at the recommended native dimensions and a quality setting of 80–90% to prevent double-compression artifacts.