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

页码：1199 / 1202

页数：4

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