Wang J, Naghdy G
School of Electrical, Computer and Telecommunication Engineering, University of Wollongong, Wollongong, NSW, Australia.
Telemed J. 2000 Summer;6(2):251-60. doi: 10.1089/107830200415199.
In this article, three novel lossless image compression schemes, hybrid predictive/vector quantization lossless image coding (HPVQ), shape-adaptive differential pulse code modulation (DPCM) (SADPCM), and shape-VQ-based hybrid ADPCM/DCT (ADPCMDCT) are introduced. All are based on the lossy coder, VQ. However, VQ is used in these new schemes as a tool to improve the decorrelation efficiency of those traditional lossless predictive coders such as DPCM, adaptive DPCM (ADPCM), and multiplicative autoregressive coding (MAR). A new kind of VQ, shape-VQ, is also introduced in this article. It provides predictive coders useful information regarding the shape characters of image block. These enhance the performance of predictive coders in the context of lossless coding. Simulation results of the proposed coders applied in lossless medical image compression are presented. Some leading lossless techniques such as DPCM, hierarchical interfold (HINT), CALIC, and the standard lossless JPEG are included in the tests. Promising results show that all these three methods are good candidates for lossless medical image compression.
本文介绍了三种新型无损图像压缩方案,即混合预测/矢量量化无损图像编码(HPVQ)、形状自适应差分脉冲编码调制(DPCM)(SADPCM)以及基于形状矢量量化的混合自适应差分脉冲编码调制/离散余弦变换(ADPCMDCT)。所有这些方案均基于有损编码器矢量量化(VQ)。然而,在这些新方案中,VQ被用作一种工具,以提高诸如DPCM、自适应DPCM(ADPCM)和乘法自回归编码(MAR)等传统无损预测编码器的去相关效率。本文还引入了一种新型矢量量化——形状矢量量化(shape-VQ)。它为预测编码器提供有关图像块形状特征的有用信息。这些在无损编码的背景下提高了预测编码器的性能。给出了所提出的编码器应用于无损医学图像压缩的仿真结果。测试中包括了一些领先的无损技术,如DPCM、分层交织(HINT)、CALIC和标准无损JPEG。有前景的结果表明,这三种方法都是无损医学图像压缩的良好候选方案。