In this paper, a procedure is reported that discuss how linear algebra can be used in image compression. The basic idea is that each image can be represented as a matrix. We apply linear algebra (QR ‎factorization and wavelet ‎transformation ‎algorithm s) on this matrix and get a reduced matrix out such that the image corresponding to this reduced matrix requires much less storage space than the original image. تفاصيل المقالة