Image Denoising Using Neural Network Based Accelerated Particle Swarm Optimization

被引：0

作者：

Mishra, Satyasis ^{[1
]}

Bisoi, Ranjeeta ^{[2
]}

机构：

[1] Centurion Univ Technol & Management, Elect & Commun Engn Dept, Bhubaneswar, Orissa, India

[2] Siksha O Anusandhan Univ, Multidisciplinary Res Cell, Bhubaneswar, Orissa, India

来源：

2015 IEEE POWER, COMMUNICATION AND INFORMATION TECHNOLOGY CONFERENCE (PCITC-2015) | 2015年

关键词：

Accelerated Particle Swarm Optimization; Median filtering; PSO; SNR; WAVELET;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a new type of filter called neural network filter for image denoising. The noisy images are fed as input to the network and the weights are updated with LMS algorithm. Further the weights are updated by using a recently developed novel optimization technique called Accelerated Particle Swarm Optimization (APSO) for gray level image denoising application. Implementation of APSO is easier than the PSO(Particle Swarm Optimization) and GA(Genetic Algorithm) in terms of computational time. The results of comparison of the optimization has been presented.

引用

页码：901 / 904

页数：4

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