How Image Compression Works: Perceptual Balance
What happens when a file gets smaller, why quality sometimes changes, and how Squeeze finds the optimal balance using perceptual metrics.
Zero-Upload Client Architecture Research
Image Compression reduces file weight by removing redundant data. Lossless compression reorganizes identical pixel values without changing visual output. Lossy compression discards subtle high-frequency color variations that the human eye cannot easily distinguish. Squeeze targets a Structural Similarity Index (SSIM) threshold ≥ 0.95, achieving up to 80% file size reduction with zero perceptible visual degradation.
Lossless vs. Lossy: The Real Difference
Lossless means the image looks identical down to the exact mathematical byte values after compression. PNG to PNG compression is always lossless. Lossy means subtle high-frequency details are discarded to make the file significantly smaller. JPG and WebP support lossy encoding.
Perceptual SSIM Scoring
Standard compression tools pick a generic quality number (like 80%), which can ruin detailed illustrations or leave simple photos unnecessarily large. Squeeze measures the mathematical structural similarity of compressed pixels against the source image, finding the exact sweet spot where visual differences remain undetectable to the human eye.
Ready to convert or compress images with 100% privacy?
Experience zero server uploads. All WebP, PNG, JPG, SVG, and multi-resolution ICO conversions run entirely inside your browser using sandboxed Web Workers.