IBM Corp., Endicott, NY.
IEEE Trans Image Process. 1996;5(2):387-92. doi: 10.1109/83.480776.
A new coding scheme based on the scalar-vector quantizer (SVQ) is developed for compression of medical images. The SVQ is a fixed rate encoder and its rate-distortion performance is close to that of optimal entropy-constrained scalar quantizers (ECSQs) for memoryless sources. The use of a fixed-rate quantizer is expected to eliminate some of the complexity of using variable-length scalar quantizers. When transmission of images over noisy channels is considered, our coding scheme does not suffer from error propagation that is typical of coding schemes using variable-length codes. For a set of magnetic resonance (MR) images, coding results obtained from SVQ and ECSQ at low bit rates are indistinguishable. Furthermore, our encoded images are perceptually indistinguishable from the original when displayed on a monitor. This makes our SVQ-based coder an attractive compression scheme for picture archiving and communication systems (PACS). PACS are currently under study for use in an all-digital radiology environment in hospitals, where reliable transmission, storage, and high fidelity reconstruction of images are desired.
一种基于标量-矢量量化器（SVQ）的新编码方案被开发出来用于医学图像的压缩。SVQ 是一种固定码率编码器，其率失真性能接近无记忆源的最优熵约束标量量化器（ECSQ）。使用固定码率量化器有望消除使用变长标量量化器的一些复杂性。当考虑通过噪声信道传输图像时，我们的编码方案不会遭受使用变长码的编码方案中典型的误差传播。对于一组磁共振（MR）图像，在低比特率下从 SVQ 和 ECSQ 获得的编码结果无法区分。此外，当在监视器上显示时，我们编码的图像在感知上与原始图像无法区分。这使得我们基于 SVQ 的编码器成为图像存档和通信系统（PACS）的一种有吸引力的压缩方案。PACS 目前正在研究用于医院中的全数字放射学环境，其中需要可靠的传输、存储和高保真度的图像重建。
