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.