一种基于格雷码的TNAM优化策略  

Gray code-based optimization strategy for TNAM

作　　者：郑运平[1] 

机构地区：[1]华南理工大学计算机科学与工程学院,广东广州510006

出　　处：《华中科技大学学报（自然科学版）》2010年第6期80-83,共4页Journal of Huazhong University of Science and Technology(Natural Science Edition)

基　　金：国家高技术研究发展计划资助项目(2006AA04Z211)

摘　　要：为了进一步提高三角形非对称逆布局模型(TNAM)表示的效率,根据格雷码(Gray code)的所有相邻整数在它们的数字表示中只有一个数字不同的特点,将格雷码应用到灰度图像的位平面分解中.提出了一种基于格雷码的TNAM优化策略(简称为GTNAM优化策略).给出了GTNAM优化策略算法的形式化描述,并对其存储结构、总数据量和时空复杂性进行了分析.理论分析和实验结果表明:基于格雷码的TNAM优化策略能显著降低子模式数和节约存储空间,是一种有效的TNAM优化策略.Gray code is an encoding of numbers so that adjacent numbers have a single digit differing by 1. To improve the representation efficiency of the triangular non-symmetry and anti packing model （TNAM） further, an optimization strategy for the Gray-code-based TNAM, which is called the GTNAM optimization strategy, is proposed. A concrete algorithm of the GTNAM optimization strategy is presented and the storage structure, the total data amount, and the time and space complexities of the proposed algorithm are analyzed in detail. The theoretical and experimental results show that the GTNAM optimization strategy can greatly reduce the number of subpatterns and simultaneously save the storage room, and therefore it is an effective optimization strategy for the TNAM.

关 键 词：图像表示 格雷码 优化 策略 三角形非对称逆布局模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]