USED EIGENVALUES AND EIGENVECTORS TO COMPRESS THE IMAGE

Abstract

The article’s main aim is to point out the significant applications of the linear algebra in the medical engineering field. Hence, the eigenvectors and eigenvalues which represent the core of linear algebra are discussed in details in order to show how they can be used in many engineering applications. The principal components analysis is one of the most important compression and feature extraction algorithms used in the engineering field (1). It mainly depends on the calculation and extraction of eigenvalues and eigenvectors that then used to represent an input; whether it's the image or a simple matrix. In this article, the use of principal component analysis for medical image compression is an important and novel application of linear algebra (2).