Nonlinear cellular neural filtering for noise reduction and extraction of image details

被引：7

作者：

Aizenberg, IN ^{[1
]}

Aizenberg, NN ^{[1
]}

Agaian, S ^{[1
]}

Astola, JT ^{[1
]}

Egiazarian, K ^{[1
]}

机构：

[1] INA, NNA, UA-294015 Uzhgorod, Ukraine

来源：

NONLINEAR IMAGE PROCESSING X | 1999年 / 3646卷

关键词：

nonlinear filtering; noise reduction; extraction of details; edge detection;

D O I：

10.1117/12.341075

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Nonlinear cellular neural filters (NCNF) are based on the non-linearity of the activation functions of universal binary neuron (UBN) and multi-valued neuron (MVN). NCNF, which include the multi-valued non-linear filters (MVF) and cellular Boolean filters (CBF), their applications are presented in details in this paper. The following problems are considered in the paper: 1) NCNF in general as a class of nonlinear filters, which includes multi-valued and cellular Boolean filters based on similar complex non-linearities; 2) Multi-valued filters as a nonlinear generalization of the simple low-pass and mean filters; 3) Connection of the multi-valued filters with other nonlinear filters; 4) Cellular Boolean filters; 5)Application of the NCNF to noise reduction; 6) Application of the NCNF to the extraction of image details; 7) Application of the NCNF to precise edge detection, edge detection by narrow direction, and image segmentation.

引用

页码：100 / 111

页数：12

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