计算机科学
远程医疗
数据压缩
图像压缩
编码(社会科学)
远程医疗
计算机视觉
多媒体
人工智能
图像处理
图像(数学)
数学
经济增长
统计
医疗保健
经济
作者
Yixiao Wang,Hamid Reza Tohidypour,Mahsa T. Pourazad,P. Nasiopoulo,Victor C. M. Leung
标识
DOI:10.1109/icce56470.2023.10043402
摘要
Telehealth applications, such as remote diagnosis and examination, have become more and more popular nowadays. However, the generated large number of medical images and their impractical digital size when it comes to telehealth have brought pressure on communication infrastructures. More specifically, the image processing time has increased dramatically due to the size of the digitized images, while requiring substantial transmission bandwidth and storage space. For these reasons, medical image compression has become a hot research topic. While image compression techniques have evolved over several generations, it remains an open question how these standards will perform when it comes to sensitive oversized medical image content. In this paper, the emerging compression standard High Efficiency Video Coding (HEVC) and the next generation standard Versatile Video Coding (VVC) are evaluated on two different medical image datasets, covering the entire range of quality levels. The results of this study show that the VVC standard overperforms HEVC on raw medical image compression both visually and quantitatively, with the performance gap narrowing when dealing with pre-compressed medical images.
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