近无损图像压缩：最小熵、约束误差 DPCM。

Near-lossless image compression: minimum-entropy, constrained-error DPCM.

机构信息

Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ 85721, USA.

出版信息

IEEE Trans Image Process. 1998;7(2):225-8. doi: 10.1109/83.660999.

Abstract

A near-lossless image compression scheme is presented. It is essentially a differential pulse code modulation (DPCM) system with a mechanism incorporated to minimize the entropy of the quantized prediction error sequence. With a "near-lossless" criterion of no more than a d gray-level error for each pixel, where d is a small nonnegative integer, trellises describing all allowable quantized prediction error sequences are constructed. A set of "contexts" is defined for the conditioning prediction error model and an algorithm that produces minimum entropy conditioned on the contexts is presented. Finally, experimental results are given.

摘要

提出了一种近无损图像压缩方案。它本质上是一种差分脉冲编码调制（DPCM）系统，其中包含一种机制，可将量化预测误差序列的熵最小化。对于每个像素，“近无损”标准不超过 d 个灰度级误差，其中 d 是一个小的非负整数，构建描述所有允许的量化预测误差序列的网格。为条件预测误差模型定义了一组“上下文”，并提出了一种根据上下文生成最小熵的算法。最后，给出了实验结果。