Online Image Resizer
Resize raster images to custom pixel dimensions or percentages with crisp scaling.
Resize JPEG, PNG, and WebP images locally with aspect-ratio controls, percentage scaling, conservative pixel limits, and browser-supported output encoding.
Use Online Image Resizer
Supports JPEG, PNG, and WebP (up to 50 MB). 100% private client-side processing.
Built for the task, not the page view
- Width/height controls with bidirectional aspect-ratio locking
- Percentage scaling from 10% to 200% plus common dimension presets
- Canvas image smoothing with high-quality browser hint where supported
- JPEG/WebP quality control and lossless PNG output
- Local preview, file-size comparison, download, and resource cleanup
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Bidirectional Aspect Ratio Locking
Locking aspect ratio keeps proportions constant. Adjusting width recalculates height (width ÷ original ratio) and adjusting height recalculates width (height × original ratio). When aspect ratio is unlocked, dimensions can be set independently, which will non-uniformly scale (stretch or squeeze) the image.
Percentage Scaling (10% to 200%)
Scale proportionally from 10% to 200% with a single slider. 50% cuts width and height in half (reducing total pixel area by 75%), while 200% doubles width and height. Scale is calculated from the original source dimensions to prevent accumulated rounding drift.
Downscaling vs. Upscaling Quality
Downscaling averages neighboring pixels smoothly. Upscaling stretches existing pixels across a larger canvas; mathematical interpolation cannot synthesize missing high-frequency details. Upscaling above 100% will result in softening or blurriness.
Canvas Image Smoothing Specs
Resizing uses the Canvas 2D API with imageSmoothingEnabled enabled and imageSmoothingQuality requested as "high" where supported. That setting is a browser quality hint, not a promise of a particular bicubic, bilinear, GPU, or other resampling algorithm.
EXIF Orientation & Metadata Handling
Browser decoding commonly honors orientation metadata, but behavior can vary by API, browser, and version; use the visual preview and exported result as the authority. Canvas re-encoding does not intentionally preserve original metadata and commonly drops EXIF/IPTC/XMP blocks; users with sensitive metadata should verify exported files if that property matters.
100% In-Browser Privacy Guarantee
All decoding, canvas manipulation, and file re-encoding occur purely in your browser memory on your device CPU/graphics subsystem. Image file bytes are never uploaded to any remote server or EveryTools API. Analytics records only fixed UI event identifiers, never your image pixels, file contents, or file names.
In-Depth Browser Image Resizing Specifications
Aspect Ratio Math & Distortion Prevention
An image's aspect ratio represents the proportional relationship between its width and height (width ÷ height). For example, a 1920×1080 pixel photo has a 16:9 ratio (1.7778), while an Open Graph banner of 1200×630 pixels has a 1.9048 ratio.
When aspect ratio is locked, any modification to width recalculates height as Math.round(width ÷ ratio). Applying a preset with a different aspect ratio will either crop, pad, or non-uniformly stretch the pixels. This tool applies exact preset dimensions by unlocking the aspect ratio and warning that non-uniform scaling will alter the image proportions.
Canvas Smoothing & Interpolation Pipeline
When an image is scaled onto an HTML5 <canvas>, the 2D rendering context uses pixel interpolation. Setting imageSmoothingEnabled = true and imageSmoothingQuality = 'high' instructs the browser to apply its highest quality resampling filter.
The exact resampling algorithm is selected by the browser and graphics stack and can vary by browser, operating system, image size, and device. The quality hint requests higher-quality interpolation where supported, but EveryTools does not claim a guaranteed bicubic, bilinear, GPU, or other specific implementation.
EXIF Orientation & Metadata Handling
Digital cameras and smartphones write EXIF tags into raw image headers containing orientation flags, camera serial numbers, focal lengths, capture timestamps, and GPS coordinates.
Browser decoding through createImageBitmap or HTMLImageElement commonly honors orientation metadata, but behavior can vary by API, browser, and version; the visual preview and exported image are the authority. Drawing decoded pixels to a canvas and re-encoding with canvas.toBlob() does not intentionally preserve the original EXIF, IPTC, or XMP metadata and commonly drops it. If removal of sensitive metadata is critical, verify the exported file rather than assuming universal stripping behavior.
Application Memory Safety Limits
Uncompressed image buffers consume substantial system memory: an uncompressed 32-bit RGBA canvas requires 4 bytes per pixel (width × height × 4). A 32-megapixel image requires approximately 128 MB of contiguous memory buffer alone.
Browser canvas limits vary by engine, operating system, and available memory. EveryTools therefore imposes conservative safety limits of 16,384px on either side and 32 megapixels total canvas area to reduce the risk of excessive memory allocation; these are application guardrails, not guaranteed browser ceilings or a guarantee that every device can process an image at the limit.
Format Selection & File Size Comparison
The output file size depends on both pixel count and chosen compression codec:
- WebP: Modern web codec offering superior compression efficiency. Supports both lossy and lossless modes, alpha transparency, and typically yields 25%–35% smaller file sizes than JPEG at comparable quality.
- JPEG: Universal standard for continuous-tone photography. Uses discrete cosine transform (DCT) lossy compression with adjustable quality (0.1 to 1.0). Does not support alpha transparency.
- PNG: Lossless format utilizing Deflate compression with predictive filtering. Ideal for line art, screenshots, and graphics requiring alpha transparency. The quality slider is ignored because Canvas PNG encoding is strictly lossless.
Frequently Asked Questions
Does resizing an image reduce its file size?
Yes, downscaling significantly reduces file size because fewer pixels must be encoded. For example, scaling an image to 50% cuts total pixel count by 75%, resulting in a dramatically smaller file.
Can I upscale small images without quality loss?
No. Upscaling stretches existing pixels across a larger resolution. Mathematical interpolation can smooth jagged edges, but cannot invent high-frequency optical details that were never captured.