Medical image compression using vector quantization and system error compression

作者：Phanprasit Tanasak; Hamamoto Kazuhiko; Sangworasil Manas; Pintavirooj Chuchart^*

来源：IEEJ Transactions on Electrical and Electronic Engineering, 2015, 10(5): 554-566.

DOI：10.1002/tee.22119

• vector quantization
• discrete wavelet transform
• fuzzy C-means
• Huffman coding
• support vector machine

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.

• 出版日期2015-9