3D SOM Neighborhood Algorithm

被引:0
|
作者
Li, Hongsong [1 ]
Cheng, Fulin [1 ]
Wang, Yanhua [1 ]
Ai, Xinyu [1 ]
机构
[1] Guilin Univ Elect Technol, Sch Informat & Commun, Guilin, Guangxi, Peoples R China
关键词
self-organizing maps; three-dimensional image coding; pattern recognition; neighborhood algorithm; SYSTEM;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Neighborhood algorithm is an important part of 3D SOM algorithm. We proposed three kinds of neighborhood shape and two kinds of neighborhood decay function for three-dimensional self-organizing feature maps (3D SOM) algorithm and applied them to three-dimensional image compression coding. Experimental results show that the 3D orthogonal cross neighborhood shape and exponential function algorithm have better peak signal to noise ratio (PSNR) and subject quality than others.
引用
收藏
页码:162 / 164
页数:3
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