An intelligent post processing technique for image enhancement

R. Pushpavalli, G. Sivarajde
{"title":"An intelligent post processing technique for image enhancement","authors":"R. Pushpavalli, G. Sivarajde","doi":"10.1109/ICEVENT.2013.6496555","DOIUrl":null,"url":null,"abstract":"An intelligent filtering technique for image enhancement is proposed in this paper. The proposed intelligent filter is carried out in two stages. In first stage the corrupted image is filtered by applying a special class of switching median filter. Filtered output image is suitably combined with a feed forward neural network in the second stage. The internal parameters of the feed forward neural network are adaptively optimized by training for three well known images. This is quite effective in eliminating impulse noise. Simulation results show that the proposed filter is superior in terms of eliminating impulse noise as well as preserving edges and fine details of digital images. The results are compared with other existing filters for performance evaluation.","PeriodicalId":6426,"journal":{"name":"2013 International Conference on Emerging Trends in VLSI, Embedded System, Nano Electronics and Telecommunication System (ICEVENT)","volume":"31 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Emerging Trends in VLSI, Embedded System, Nano Electronics and Telecommunication System (ICEVENT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEVENT.2013.6496555","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

An intelligent filtering technique for image enhancement is proposed in this paper. The proposed intelligent filter is carried out in two stages. In first stage the corrupted image is filtered by applying a special class of switching median filter. Filtered output image is suitably combined with a feed forward neural network in the second stage. The internal parameters of the feed forward neural network are adaptively optimized by training for three well known images. This is quite effective in eliminating impulse noise. Simulation results show that the proposed filter is superior in terms of eliminating impulse noise as well as preserving edges and fine details of digital images. The results are compared with other existing filters for performance evaluation.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
一种图像增强的智能后处理技术
提出了一种用于图像增强的智能滤波技术。所提出的智能滤波分两个阶段进行。在第一阶段,使用一类特殊的切换中值滤波器对损坏图像进行滤波。在第二阶段,将滤波后的输出图像与前馈神经网络适当结合。通过对三幅已知图像的训练,自适应优化前馈神经网络的内部参数。这在消除脉冲噪声方面非常有效。仿真结果表明,该滤波器在消除脉冲噪声、保留数字图像边缘和细节方面具有较好的效果。将结果与其他现有滤波器进行了性能评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Augmented Reality based 3D commercial advertisements Modeling the inversion charge centroid in Tri-Gate MOSFETs including quantum effects Separable extraction of concealed data and compressed image Design of 2∶1 multiplexer and 1∶2 demultiplexer using magnetic tunnel junction elements Potential and electric field model for 18 nm SG tunnel field effect transistor
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1