期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2020
卷号：98
期号：19
页码：3076-3087
出版社：Journal of Theoretical and Applied
摘要：Over the last few decades, image reconstruction has become an interesting field for the development of computer-based applications. The Decomposition of a matrix or matrix factorization is one of the most important components in many engineering and scientific applications. This technique is used to decompose one matrix into more than one matrix. One can efficiently solve a system of equations based on matrix factorization, and this, in turn, is the foundation of the inverse matrix, which is a major component of several important algorithms. Matrix factorizations are widely applied in situations that involve solving linear systems, numerical linear algebra, rank estimation, image processing, image reconstruction etc. This paper attempts to analyze the techniques of matrix factorization or decomposition techniques used in image reconstruction based on their advantages, disadvantages, limitations and computation complexity. Some techniques are examined and a comparative evaluation of these strategies is presented. This paper also shows the homogeneity between the Fourier series and matrix factorization process in image reconstruction.
