Burrows-Wheeler Transformation for Medical Image Compression

Aierken Shalayiding, Z. Arnavut, B. Koc, H. Kocak
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Abstract

Medical imaging is a very useful component in diagnosing diseases. For future use, and further study and analysis, hospitals must keep all patients' medical images in databases. In this work, a new lossless image compression technique is proposed for efficient storage and transmission of medical images. The newly proposed technique is based on encoding prediction errors with a suitable entropy coder upon transforming them with the Burrows-Wheeler Transformation (BWT). We show that the newly proposed technique yields better compression than the mainstream lossless compression algorithms JPEG-2000 and JPEG-LS.
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医学图像压缩中的Burrows-Wheeler变换
医学影像是诊断疾病的一个非常有用的组成部分。为了将来使用和进一步研究和分析,医院必须将所有患者的医学图像保存在数据库中。本文提出了一种新的无损图像压缩技术,用于医学图像的高效存储和传输。该方法是利用Burrows-Wheeler变换(BWT)对预测误差进行编码,并选择合适的熵码对预测误差进行编码。结果表明,该方法比主流的无损压缩算法JPEG-2000和JPEG-LS具有更好的压缩效果。
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