Glenn M E
MITRE Corporation, Civil Systems Division, McLean, Virginia 22102.
J Med Syst. 1987 Jun;11(2-3):149-56. doi: 10.1007/BF00992349.
The physical size of typical digital images, in terms of the number of bytes of data one image contains, is large; e.g., a 1024 X 1024 image with 8 bits of data per pixel contains a megabyte of data. To transmit many such images over a network, sometimes over low-capacity phone lines to remote sites, or to store large numbers of images over a long period of time as part of the medical records for patients, the need for image compression arises to alleviate these large demands for image data storage and transmission capacity. This paper discusses image compression in terms of the information theory upon which it is based. The two basic categories of algorithms for implementing image compression are presented along with considerations for image quality and accuracy, which are of primary importance to the medical imaging community.
就一幅图像所包含的数据字节数而言,典型数字图像的物理尺寸很大;例如,一幅1024×1024的图像,每个像素有8位数据,就包含一兆字节的数据。为了通过网络传输许多这样的图像(有时要通过低容量电话线传输到远程站点),或者作为患者病历的一部分长时间存储大量图像,就需要进行图像压缩,以缓解对图像数据存储和传输容量的巨大需求。本文从其基于的信息论角度讨论图像压缩。介绍了实现图像压缩的两种基本算法类别,以及对图像质量和准确性的考量,这些对医学成像领域至关重要。