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
收藏
页码：1231 / 1236
页数：6
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