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How to Compress Images Online — JPG, PNG, WebP Compression Guide

Learn how image compression works — lossy vs lossless, how JPG/PNG/WebP compression differs, what quality setting to choose, and how to batch-compress images without losing visible quality.

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Core Concepts

Lossy vs lossless compression
Lossy compression (JPG, WebP lossy, AVIF lossy) permanently discards visual data the human eye is unlikely to notice — smaller files, some quality loss. Lossless compression (PNG, WebP lossless) reduces file size without any quality loss — bigger files, perfect fidelity. Choose lossy for photos and web images (50-80% smaller). Choose lossless for logos, line art, and images that contain text.
How to pick the right quality setting
JPG at quality 80% is the sweet spot — indistinguishable from 100% for most photos, but 3-5× smaller. PNG compression reduces file size by optimising the DEFLATE algorithm parameters without any visual change. WebP at -q 75 typically halves the size of an equivalent JPG. The best approach: use comparison mode and slide between original and compressed to find the lowest quality that still looks good.
Batch compression and resizing
For a blog post with 20 images, compressing each one individually is tedious. Batch tools let you drop a folder, apply the same settings to all images, and download as a ZIP. Also consider resizing: a 4000px-wide photo scaled to 1200px (the widest most websites display) can save 70% of the file size before any compression even starts.

Frequently Asked Questions

Does compressing an image reduce quality?

Lossy compression: yes, but subtly. At JPG quality 80%, the difference is invisible on a phone screen. At quality 50%, you'll see blocky artifacts (compression squares) in gradients and sky areas. Lossless compression: no quality loss at all — PNG compression is mathematically reversible.

How do I compress images without uploading them to a server?

All compression in our Image Compressor runs in your browser via canvas, Web Workers, and native compression codecs. The image is loaded into a canvas element, re-encoded at the chosen quality, and saved locally. The browser's DevTools Network panel confirms zero HTTP requests during compression.

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