Three novel lossless image compression schemes for medical image archiving and telemedicine.

J Wang, G Naghdy
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引用次数: 8

Abstract

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.

用于医学图像存档和远程医疗的三种新的无损图像压缩方案。
本文介绍了三种新的无损图像压缩方案: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(SADPCM)和基于形状vq的混合ADPCM/DCT (ADPCMDCT)。所有这些都是基于有损编码器,VQ。然而,在这些新方案中,VQ作为一种工具来提高传统的无损预测编码如DPCM、自适应DPCM (ADPCM)和乘式自回归编码(MAR)的去相关效率。本文还介绍了一种新的VQ - shape-VQ。它为预测编码器提供了有关图像块形状特征的有用信息。这些改进了在无损编码环境下预测编码器的性能。给出了该编码器在医学图像无损压缩中的应用仿真结果。测试中包括一些领先的无损技术,如DPCM、分层交叉(HINT)、CALIC和标准无损JPEG。结果表明,这三种方法都是医学图像无损压缩的理想选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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