Open AccessImage Compression Techniques Using Linear Algebra with SVD Algorithm
Author(s) -
Sundaraelangovan Selvam,
Surya Selvam
Publication year - 2021
Publication title -
asian journal of engineering and applied technology
Language(s) - English
Resource type - Journals
ISSN - 2249-068X
DOI - 10.51983/ajeat-2021.10.1.2724
Subject(s) - lossy compression , computer science , lossless compression , data compression , python (programming language) , singular value decomposition , image compression , algorithm , data compression ratio , artificial intelligence , image processing , image (mathematics) , programming language
In recent days, the data are transformed in the form of multimedia data such as images, graphics, audio and video. Multimedia data require a huge amount of storage capacity and transmission bandwidth. Consequently, data compression is used for reducing the data redundancy and serves more storage of data. In this paper, addresses the problem (demerits) of the lossy compression of images. This proposed method is deals on SVD Power Method that overcomes the demerits of Python SVD function. In our experimental result shows superiority of proposed compression method over those of Python SVD function and some various compression techniques. In addition, the proposed method also provides different degrees of error flexibility, which give minimum of execution of time and a better image compression.