How Image Compression Works: Algorithms Explained

How Image Compression Works: Algorithms Explained A raw 1920×1080 RGB photo is 6.2 MB. The JPEG you actually use is 300 KB. That 20:1 ratio isn't magic — it's the result of sequential steps that exploit how human vision works. Understanding those steps changes how you make compression decisions. Why Images Need Compression Raw pixel data is brutal. Each pixel needs three bytes (one each for red, green, blue). A 1920×1080 image has 2,073,600 pixels × 3 bytes = 6,220,800 bytes — over 6 MB for a single photo. Multiply that by the hundreds of images on a typical website, and you've got a bandwidth problem. The solution: represent the same visual information with far fewer bytes by throwing out what the human eye won't notice anyway. The Two Families: Lossy and Lossless Every compression algorithm belongs to one of two families: Lossy compression permanently discards information. You get smaller files, but you can never recover the original exactly. JPEG, WebP (default), and AVIF are lossy