Best Parameters Selection for Wavelet Packet-Based Compression of Magnetic Resonance Images

Computers and biomedical research, an international journal Pub Date : 1999-10-01 DOI:10.1006/cbmr.1999.1523

A.N. Abu-Rezq , A.S. Tolba , G.A. Khuwaja , S.G. Foda

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引用次数: 16

Abstract

Transmission of compressed medical images is becoming a vital tool in telemedicine. Thus new methods are needed for efficient image compression. This study discovers the best design parameters for a data compression scheme applied to digital magnetic resonance (MR) images. The proposed technique aims at reducing the transmission cost while preserving the diagnostic information. By selecting the wavelet packet's filters, decomposition level, and subbands that are better adapted to the frequency characteristics of the image, one may achieve better image representation in the sense of lower entropy or minimal distortion. Experimental results show that the selection of the best parameters has a dramatic effect on the data compression rate of MR images. In all cases, decomposition at three or four levels with the Coiflet 5 wavelet (Coif 5) results in better compression performance than the other wavelets. Image resolution is found to have a remarkable effect on the compression rate.

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基于小波包的磁共振图像压缩最佳参数选择

压缩医学图像的传输正在成为远程医疗的重要工具。因此，需要新的方法来实现高效的图像压缩。本研究发现了应用于数字磁共振(MR)图像的数据压缩方案的最佳设计参数。该技术旨在降低传输成本，同时保留诊断信息。通过选择更适合图像频率特性的小波包滤波器、分解级别和子带，可以在较低熵或最小失真的意义上实现更好的图像表示。实验结果表明，最佳参数的选择对MR图像的数据压缩率有显著影响。在所有情况下，使用Coiflet 5小波(Coiflet 5)在三或四层进行分解的结果比其他小波具有更好的压缩性能。图像分辨率对压缩率有显著的影响。

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Computers and biomedical research, an international journal

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