Image Compression using Singular Value Decomposition

Abstract

The Singular Value Decomposition expresses image data in terms of number of Eigen vectors depending upon the dimension of an image. The psycho visual redundancies in an image are used for compression. Thus an image can be compressed without affecting the image quality. This paper presents one such image compression technique called as {SVD}. Basic mathematics of {SVD} is dealt with in detail and results of applying {SVD} on an image are also discussed. The {MSE} and compression ratio are used as thresholding, parameters for reconstruction. {SVD} is applied on variety of images for experimentation. The work is concentrated to reduce the number of eigen values required to reconstruct an image.