Compressing an image and expecting the result to look identical to the original, just smaller, is a reasonable-sounding expectation that doesn't survive contact with how image compression actually works. Understanding where the visible quality loss in a heavily compressed image actually comes from — and why it shows up in some specific, predictable places rather than uniformly across the whole image — makes it much easier to choose a compression level that balances file size against acceptable visual quality.
Compression works by discarding information, not by being clever about storage
Lossy image compression, the kind used by JPEG and lossy WebP, achieves smaller file sizes specifically by discarding some of the original image's information — not by finding some clever, magical way to store the exact same information in less space. This is a fundamentally different approach from lossless compression (used by PNG and lossless WebP), which achieves smaller file sizes purely through smarter, information-preserving encoding, with zero data loss. Lossy compression's entire strategy is deciding which information can be discarded with the least perceptible visual impact, and understanding that strategy explains exactly where visible artifacts show up when the compression level is pushed too aggressively.
Why compression artifacts cluster around sharp edges
JPEG-style compression works by breaking an image into small blocks and representing each block's content using a mathematical transformation that's efficient at capturing smooth, gradual variation but comparatively inefficient at capturing sharp, sudden transitions. This is exactly why compression artifacts characteristically appear as blockiness or ringing specifically around sharp edges — text, hard object boundaries, high-contrast transitions — while smooth, gradually varying areas like sky, skin, or blurred backgrounds tend to compress with far less visible quality loss even at fairly aggressive compression settings. This asymmetry is also the underlying reason JPEG handles photographs (which are mostly smooth gradual variation) far better than sharp-edged graphics like text or logos (where the same compression approach introduces obvious, ugly artifacts).
Color information gets compressed more aggressively than brightness information
A detail that surprises many people: JPEG compression typically discards more color detail than brightness detail, a technique called chroma subsampling, based on research showing human vision is considerably more sensitive to fine detail in brightness than in color. This means two images with identical brightness patterns but different levels of fine color detail can end up looking similarly sharp after compression, even though the color information was compressed away more aggressively than the brightness information — the compression is deliberately exploiting a known limitation in human visual perception rather than treating all image information as equally important to preserve.
Why saving a JPEG multiple times makes it progressively worse
Every time a JPEG is re-saved after being edited, the lossy compression process runs again on an already-compressed image, discarding additional information on top of whatever was already lost in the previous save. This compounding effect, sometimes called "generation loss," is why repeatedly opening, lightly editing, and re-saving the same JPEG file multiple times produces a visibly worse result than making all the same edits in one single editing session and saving once — each additional compression pass introduces its own new artifacts stacked on top of whatever the previous passes already introduced, and this compounds noticeably faster than most people expect from what feels like a series of individually minor edits.
Why keeping an uncompressed or losslessly-compressed master matters
Given the generation-loss issue above, a common and genuinely important practice for anyone doing repeated image editing is keeping an original, uncompressed or losslessly-compressed master file, and only exporting a lossy-compressed version (like a JPEG) as the final output step, after all editing is complete — rather than repeatedly editing and re-saving the same already-lossy-compressed file over and over. This avoids the compounding generation loss entirely, since each export from the pristine master starts from full-quality source data rather than building additional loss on top of previous compression passes.
Finding the right compression level for your actual use case
Because compression artifacts specifically target sharp edges and fine color detail rather than affecting an image uniformly, the "right" compression level genuinely depends on the specific image content — a photo with mostly smooth gradual variation and no fine text can often tolerate fairly aggressive compression with minimal visible quality loss, while an image containing sharp text, fine patterns, or high-contrast detail will show artifacts at a compression level that would look perfectly acceptable on a smoother, less detailed photo. This is exactly why there's no single universally "correct" compression percentage — it depends on what's actually in the specific image being compressed.
Compressing your own images
Our image compressor lets you adjust the compression level and preview the result directly, which is the most reliable way to find the right balance for a specific image's own content — since, per everything above, the right setting genuinely varies depending on what's actually in the picture rather than following one universal rule.