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首页> 外文期刊>Research journal of applied science, engineering and technology >Volumetric Medical Images Lossy Compression using Stationary Wavelet Transform and Linde-Buzo-Gray Vector Quantization
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Volumetric Medical Images Lossy Compression using Stationary Wavelet Transform and Linde-Buzo-Gray Vector Quantization

机译:使用固定小波变换和Linde-Buzo-Gray矢量量化的体积医学图像有损压缩

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摘要

The aim of the study is to reduce the size required for storage along with decreasing the bitrate and the bandwidth for the process of sending and receiving the image. It also aims to decrease the time required for the process as much as possible. This study proposes a novel system for efficient lossy volumetric medical image compression using Stationary Wavelet Transform and Linde-Buzo-Gray for Vector Quantization. The system makes use of a combination of Linde-Buzo-Gray vector quantization technique for lossy compression along with Arithmetic coding and Huffman coding for lossless compression. The system proposed uses Stationary Wavelet Transform and then compares the results obtained to Discrete Wavelet Transform, Lifting Wavelet Transform and Discrete Cosine Transform at three decomposition levels. The system also compares the results obtained using transforms with only Arithmetic Coding and Huffman Coding for Lossless Compression.The results show that the system proposed outperforms the others.
机译:该研究的目的是减小存储所需的大小,同时降低发送和接收图像过程的比特率和带宽。它还旨在尽可能减少该过程所需的时间。这项研究提出了一种新颖的系统,该系统使用固定小波变换和Linde-Buzo-Gray进行矢量量化,可以有效地进行有损容积医学图像压缩。该系统结合了用于有损压缩的Linde-Buzo-Gray矢量量化技术以及用于无损压缩的算术编码和霍夫曼编码。提出的系统使用平稳小波变换,然后将获得的结果与离散小波变换,提升小波变换和离散余弦变换在三个分解级别上进行比较。该系统还比较了仅使用算术编码和霍夫曼编码进行无损压缩的变换结果,结果表明该系统优于其他算法。

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