Volume 6, Issue 4, December 2018, Page: 116-120
The Application of Selective Image Compression Techniques
Ikerionwu Charles, Department of Information Technology, School of Computing and Information Technology, Federal University of Technology, Owerri, Nigeria
Isonkobong Christopher Udousoro, Department of Information Technology, School of Computing and Information Technology, Federal University of Technology, Owerri, Nigeria
Received: Dec. 9, 2018;       Accepted: Dec. 22, 2018;       Published: Jan. 16, 2019
DOI: 10.11648/j.se.20180604.12      View  312      Downloads  54
Abstract
The limited available storage and bandwidth required for successful transmission of large images make image compression a key component in digital image transmission. Digital image application in various industries, such as entertainment and advertising, has brought image processing to the fore of these industries. However, the entire image processing is faced with the problem of data redundancy, which is mitigated through image compression. This is simply the art and science of reducing the number of bits/data of an image before it is transmitted and stored easily while the quality of image is maintained. Thus, through an exploratory study, this paper examines image compression as discussed in extant literature and emphasises on different methods used in image compression. The paper reviewed relevant literature from Elsevier, Emerald, IEEE, ProQuest and Google scholar databases. Specific methods are lossy and lossless techniques, which are further divided into run length encoding, and entropy encoding. In conclusion, the paper recommends compression techniques to adopt depending on the industry’s’ goals. Preferably, lossy compression is used to compress multimedia data which includes audio, video and images, while lossless compression technique is used to compress text and data files.
Keywords
Image Compression, Lossy Technique, Lossless Technique, Transform Coding Encoder and Decoder
To cite this article
Ikerionwu Charles, Isonkobong Christopher Udousoro, The Application of Selective Image Compression Techniques, Software Engineering. Vol. 6, No. 4, 2018, pp. 116-120. doi: 10.11648/j.se.20180604.12
Copyright
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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