一种用于贝尔模板图像压缩的算术编码器  

A Novel Arithmetic Coder for Bayer Pattern Images Compression

作　　者：程永强[1] 刘康[1] 谢克明[1] 张刚[1] 

机构地区：[1]太原理工大学信息工程学院,山西太原030024

出　　处：《中北大学学报（自然科学版）》2009年第5期462-466,共5页Journal of North University of China(Natural Science Edition)

基　　金：国家自然科学基金资助项目(60372058);山西省自然科学基金资助项目(20051019)

摘　　要：针对贝尔模板图像的预测编码问题,设计了一种高效的自适应算术编码器.通常,贝尔模板图像的预测误差满足拉普拉斯分布,为了降低估计预测误差概率的计算复杂度,按照最小均方误差准则对预测误差进行了分类量化,并建立了相应的概率查找表,概率值仅需要保留3位有效值.实验结果表明:提出的算术编码器比Golomb熵编码方法具有更高的效率.Aiming at the coding of prediction errors based on the Bayer pattern images, an effective and adaptive arithmetic coder is designed. Generally, a probability distribution of the prediction errors forms Laplacian distribution with zero mean. To reduce computing complexity of estimation of the error probability, the error is classified into quantization regions by minimizing mean square error, and a table is designed which lists the error quantization regions and corresponding probability with 3 significance bits. Experiment result shows that the proposed arithmetic coder is more effective than Golomb coder.

关 键 词：贝尔模板图像 预测误差 算术编码 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]