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Medical image compression using Embedded Zerotree Wavelet (EZW) coder

机译:使用嵌入式零树小波(EZW)编码器的医学图像压缩

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The aim of this paper is to investigate and explore the viability of Embedded Zerotree (EZW) wavelet coder for therapeutic and medical image compression and high lights its performance based on quality evaluation measurements comparing to Mean square Error (MSE), Bit per pixel (BPP), Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR) for a particular set of medical images of different modalities. Discrete Wavelet Transform (DWT) has turned into a front line innovation in the spheres of picture processing in general and image compression in particular due to impressive and noteworthy change in picture quality at high compression quotient and better compaction of coefficients. The algorithm what is discussed in this paper has been implemented using the wavelet toolbox of MATLAB. The simulation results exposition that the proposed algorithm is not only an option for the image storage and retrieval on the cloud based medical image computing expeditiously, effectively and economically but it also supports to enhance the utility services in telediagnosis and teleconsultation.
机译:本文的目的是研究和探索嵌入式零树(EZW)小波编码器在治疗和医学图像压缩中的可行性,并基于与均方误差(MSE),每像素比特数(BPP)相比较的质量评估结果,强调其性能。 ),不同模式的一组特定医学图像的峰值信噪比(PSNR)和压缩率(CR)。离散小波变换(DWT)已成为一般图像处理领域和图像压缩领域的一线创新,特别是由于在高压缩系数和更好的系数压缩条件下图像质量发生了令人印象深刻的变化。本文讨论的算法已使用MATLAB的小波工具箱实现。仿真结果表明,该算法不仅可以快速,有效,经济地在基于云的医学图像计算中进行图像存储和检索,还可以增强在远程诊断和远程咨询中的实用服务。

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