Noisy Image Restoration Based on Optimized Cellular Neural Network

被引：0

作者：

Aberomand, Nima ^{[1
]}

Jameii, Seyed Mandi ^{[1
]}

机构：

[1] Islamic Azad Univ, Shahr E Qods Branch, Dept Comp Engn, Tehran, Iran

来源：

2015 2ND INTERNATIONAL CONFERENCE ON KNOWLEDGE-BASED ENGINEERING AND INNOVATION (KBEI) | 2015年

关键词：

image restoration; cellular neural network; image processing; MSE; PSNR;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Sending multimedia file in computer networks from the source to destination can cause noisy. Some images have default noises. Other types of images in processing can be noisy due to high level process in weak systems. Creating a system for image retrieval is an important part of image processing. This article focused on noisy image restoration based on cellular neural network. Noises inside the pixel with different sizes are restored with different levels of surrounding information. Images with 50% of noise cannot be recovered correctly, but optimized cellular neural network can recover whole part of images with less noises. The main purposes of using cellular neural network are less time with more noise removal. Two evaluation methods like MSE and PSNR are used to compare with recent methods.

引用

页码：1194 / 1197

页数：4