Mean squared error (MSE) is the raw pixel-error measure that PSNR is built on. Read right to left, the name is the recipe: take the error at every pixel (original value minus compressed value), square it, then take the mean of all those squares across the frame. Squaring does two jobs — it makes every error positive so they do not cancel, and it punishes big errors far more than small ones. An MSE of zero means the frames are identical; a larger MSE means more error, though its scale depends on bit depth, which makes the raw number unintuitive. PSNR fixes that by rescaling MSE against the squared peak pixel value and taking a logarithm, so PSNR is, quite literally, MSE expressed in decibels. The key limitation passes to every metric built on it: MSE sums error with no model of where it landed or how the eye masks it, so two very different-looking distortions can share one MSE — the root of PSNR's weak perceptual fidelity.
