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Medical image compression using set partitioning in hierarchical trees for (military) telemedicine applications

机译:在(军事)远程医疗应用中使用分层树中的集划分的医学图像压缩

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Imagery is an important source of information both to the military and to the medical doctor. To support highly mobile forces, wireless communications are essential. However, this results in limited bandwidths available for the transmission of information, including imagery. High quality, maximum compression and fast image coding techniques are required both by the military and their field doctors for transmission over their limited bandwidth communications channels. This paper describes our ongoing research into the applicability of SPIHT image coding in a (military) telemedicine system. The performance of coding a typical medical image is also compared against the international standard, JPEG. Set Partitioning In Hierarchical Trees (SPMT) is a new image coding technique, developed by A. Said and W.A. Pearlman (1996), which orders the transform coefficients using a set partitioning algorithm based on the subband pyramid. By sending the most important information first of the ordered coefficients, the information required to reconstruct the image is extremely compact. This new technique offers significant improvement in compression ratios compared with JPEG, Wavelets and Fractals. SPIHT is also one of the fastest codecs available and provides user selectable file size or image quality and progressive image resolution and transmission.
机译:图像是军队和医生的重要信息来源。为了支持高度机动的部队,无线通信必不可少。但是,这导致有限的带宽可用于信息传输,包括图像。军事及其野外医生都需要高质量,最大压缩率和快速图像编码技术,以通过其有限的带宽通信信道进行传输。本文介绍了我们正在进行的对SPIHT图像编码在(军事)远程医疗系统中的适用性的研究。还将典型医学图像的编码性能与国际标准JPEG进行了比较。层次树中的集合划分(SPMT)是A. Said和W.A. Pearlman(1996)开发的一种新的图像编码技术,它使用基于子带金字塔的集合划分算法对变换系数进行排序。通过首先发送最重要的信息(有序系数),重建图像所需的信息非常紧凑。与JPEG,小波和分形相比,这项新技术大大提高了压缩率。 SPIHT还是最快的编解码器之一,可为用户提供可选的文件大小或图像质量以及渐进式图像分辨率和传输。

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