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首页> 外文期刊>International journal of biomedical engineering and technology >Gray scale and colour medical image compressed using hybrid contourlet biorthogonal CDF lifting scheme, bandelet and quincunx wavelet transforms: a comparative study
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Gray scale and colour medical image compressed using hybrid contourlet biorthogonal CDF lifting scheme, bandelet and quincunx wavelet transforms: a comparative study

机译:使用混合Contourlet Biorthogond CDF提升方案,Bandelet和Quincunx小波变换压缩灰度和彩色医学图像:比较研究

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摘要

The Quincunx wavelet, the lifting scheme wavelet and the second generation bandelet transform are a new method to offer an optimal representation for image geometric. In the field of medical diagnostics, interested parties have resorted increasingly to medical imaging. It is well established that the accuracy and completeness of diagnosis are initially connected with the image quality, but the quality of the image is itself dependent on a number of factors including primarily the processing that an image must undergo to enhance its quality. The quality evaluation of compressed image is necessary to judge the performance of a compression method. This paper introduces an algorithm for medical image compression based on hybrid non-subsampled contourlet (NSCT) and quincunx wavelet transforms (QWT) coupled with SPIHT coding algorithm, of which we present the objective measurements (PSNR, EDGE, WPSNR, MSSIM, VTF, and WSNR) in order to evaluate the quality of the image.
机译:Quincunx小波,提升方案小波和第二代Bandelet变换是为图像几何提供最佳表示的新方法。 在医学诊断领域,有关各方越来越多地对医学成像。 很好地确定,诊断的准确性和完整性最初与图像质量相连,但图像的质量本身取决于许多因素,包括主要是图像必须经历以提高其质量的处理。 压缩图像的质量评估是判断压缩方法的性能所必需的。 本文介绍了一种基于混合非分离的Contourlet(NSCT)和Quincunx小波变换(QWT)的医学图像压缩算法,耦合与SPIHT编码算法,其中我们提供了目标测量(PSNR,Edge,WPSNR,MSSIM,VTF, 和WSNR)为了评估图像的质量。

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