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.
