Nonlinear image interpolation by radial basis function networks

被引：0
|
作者：
Yasukawa, M [1 ]
Ikeguchi, T [1 ]
Takagi, M [1 ]
Matozaki, T [1 ]
机构：
[1] Sci Univ Tokyo, Dept Appl Elect, Noda, Chiba 278, Japan
来源：
PROGRESS IN CONNECTIONIST-BASED INFORMATION SYSTEMS, VOLS 1 AND 2 | 1998年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we proximate and interpolate gray scale surfaces of image with a nonlinear method, or radial basis function ne We evaluate interpolation performance of radial basis interpolation and linear methods by calculating signal-to-noise ratios. As a result, it is shown that interpolation with radial basis function networks is quantitatively better than linear interpolations in terms of signal-to-noise ratios.
引用
收藏
页码：1199 / 1202
页数：4
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