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     Research Journal of Applied Sciences, Engineering and Technology


Volumetric Medical Images Lossy Compression using Stationary Wavelet Transform and Linde-Buzo-Gray Vector Quantization

1Hend A. Elsayed, 2Omar G. Abood and 2Shawkat K. Guirguis
1Department of Communication and Computer Engineering Faculty of Engineering, Delta University for Science and Technology, Mansoura
2Department of Information Technology, Institute of Graduate Studies and Researches, Alexandria University, Egypt
Research Journal of Applied Sciences, Engineering and Technology  2017  9:352-360
http://dx.doi.org/10.19026/rjaset.14.5134  |  © The Author(s) 2017
Received: January 1, 2017  |  Accepted: August 14, 2017  |  Published: September15, 2017

Abstract

The aim of the study is to reduce the size required for storage along with decreasing the bitrate and the bandwidth for the process of sending and receiving the image. It also aims to decrease the time required for the process as much as possible. This study proposes a novel system for efficient lossy volumetric medical image compression using Stationary Wavelet Transform and Linde-Buzo-Gray for Vector Quantization. The system makes use of a combination of Linde-Buzo-Gray vector quantization technique for lossy compression along with Arithmetic coding and Huffman coding for lossless compression. The system proposed uses Stationary Wavelet Transform and then compares the results obtained to Discrete Wavelet Transform, Lifting Wavelet Transform and Discrete Cosine Transform at three decomposition levels. The system also compares the results obtained using transforms with only Arithmetic Coding and Huffman Coding for Lossless Compression.The results show that the system proposed outperforms the others.

Keywords:

Arithmetic coding, discrete cosine transform, discrete wavelet transform, Huffman coding, lifting wavelet transform, Linde-Buzo-gray vector quantization, Lossy compression, stationary wavelet transform , volumetric medical images,


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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