This demonstrates how an image can be compressed via the singular value decomposition (SVD). The original image is first represented as a matrix

with the intensity of each pixel assigned a numeric value. Then the singular value decomposition is performed and a low rank approximation of

is formed via

, where

is the

singular value and

and

are the

left and right singular vectors, respectively.