Type of blur and blur parameters identification using neural network and its application to image restoration

被引：0

作者：

Aizenberg, I ^{[1
]}

Bregin, T ^{[1
]}

Butakoff, C ^{[1
]}

Karnaukhov, V ^{[1
]}

Merzlyakov, N ^{[1
]}

Milukova, O ^{[1
]}

机构：

[1] Russian Acad Sci, Inst Informat Transmiss Problems, Moscow 117901, Russia

来源：

ARTIFICIAL NEURAL NETWORKS - ICANN 2002 | 2002年 / 2415卷

关键词：

neural network; image restoration; frequency domain;

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：

The original solution of the blur and blur parameters identification problem is presented in this paper. A neural network based on multi-valued neurons is used for the blur and blur parameters identification. It is shown that using simple single-layered neural network-it is possible to identify the type of the distorting operator. Four types of blur are considered: defocus, rectangular, motion and Gaussian ones. The parameters of the corresponding operator are identified using a similar neural network. After a type of blur and its parameters identification the image can be restored using several kinds of methods.

引用

页码：1231 / 1236

页数：6