Medical image compression using vector quantization and system error compression

被引：1

作者：

Phanprasit, Tanasak ^{[1
]}

Hamamoto, Kazuhiko ^{[2
]}

Sangworasil, Manas ^{[3
]}

Pintavirooj, Chuchart ^{[1
]}

机构：

[1] KMITL, Dept Elect Engn, Fac Engn, Bangkok, Thailand

[2] Tokai Univ, Sch Informat & Telecommun Engn, Dept Informat Media Technol, Tokyo 151, Japan

[3] Rangsit Univ, Dept Biomed Engn Program, Dept Phys, Fac Sci, Pathum Thani, Thailand

来源：

IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING | 2015年 / 10卷 / 05期

关键词：

vector quantization; discrete wavelet transform; fuzzy C-means; Huffman coding; support vector machine; CODEBOOK SEARCH ALGORITHM;

D O I：

10.1002/tee.22119

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A novel medical image compression scheme based on vector quantization (VQ) is proposed in this paper. The advantages of the technique are not only that it yields high compression ratio but also that it maintains a peak signal-to-noise ratio (PSNR). This new method involves three steps. First, we present a codebook design using discrete wavelet transform (DWT), fuzzy C-means (FCM), and support vector machine (SVM) algorithms. Second, we improve the bit rate using the Huffman coding theme as a method of eliminating the redundant index. Finally, we supplement the system with error compensation to improve the PSNR. With the proposed method, we are able to achieve a bit rate improvement of 24.00% and a PSNR of 10.96% over the conventional method. (c) 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

引用

页码：554 / 566

页数：13

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