基于模糊理论和人工神经网络的图像去雾性能分析

N. Minallah, I. Ullah, M. Ashfaq, H. Mahesar
{"title":"基于模糊理论和人工神经网络的图像去雾性能分析","authors":"N. Minallah, I. Ullah, M. Ashfaq, H. Mahesar","doi":"10.26692/Surj/2017.12.54","DOIUrl":null,"url":null,"abstract":"Photography in hazy environment, light attenuation and scattering caused by the water particles present in the medium, result in loss of severe image quality and loss of valuable information. In order to minimize the effect of haze and improve visual quality, this literature present a novel technique combining fuzzy theory, artificial neural networks and image fusion. Transmission map is estimated using fuzzy inference system. Then morphological operation and artificial neural network are applied to remove the halation present. Backpropagation, feedforward, cascaded-feedforward and fitnet artificial neural networks are applied on halation free transmission map for further refinement. Finally, image fusion technique is used to recover an enhanced version of all four images.","PeriodicalId":21859,"journal":{"name":"Sindh University Research Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On the Performance analysis of image Dehazing using fuzzy theory and Artificial Neural Networks\",\"authors\":\"N. Minallah, I. Ullah, M. Ashfaq, H. Mahesar\",\"doi\":\"10.26692/Surj/2017.12.54\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Photography in hazy environment, light attenuation and scattering caused by the water particles present in the medium, result in loss of severe image quality and loss of valuable information. In order to minimize the effect of haze and improve visual quality, this literature present a novel technique combining fuzzy theory, artificial neural networks and image fusion. Transmission map is estimated using fuzzy inference system. Then morphological operation and artificial neural network are applied to remove the halation present. Backpropagation, feedforward, cascaded-feedforward and fitnet artificial neural networks are applied on halation free transmission map for further refinement. Finally, image fusion technique is used to recover an enhanced version of all four images.\",\"PeriodicalId\":21859,\"journal\":{\"name\":\"Sindh University Research Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sindh University Research Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26692/Surj/2017.12.54\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sindh University Research Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26692/Surj/2017.12.54","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在雾蒙蒙的环境下摄影,由于介质中存在水粒子,造成光的衰减和散射,造成严重的图像质量损失和有价值的信息损失。为了最大限度地减少雾霾的影响,提高视觉质量,本文提出了一种结合模糊理论、人工神经网络和图像融合的新技术。利用模糊推理系统对传输图进行估计。然后运用形态学运算和人工神经网络技术对存在的色散进行去除。采用反向传播、前馈、级联前馈和fitnet人工神经网络对无振荡传输图进行进一步细化。最后,使用图像融合技术恢复所有四幅图像的增强版本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
On the Performance analysis of image Dehazing using fuzzy theory and Artificial Neural Networks
Photography in hazy environment, light attenuation and scattering caused by the water particles present in the medium, result in loss of severe image quality and loss of valuable information. In order to minimize the effect of haze and improve visual quality, this literature present a novel technique combining fuzzy theory, artificial neural networks and image fusion. Transmission map is estimated using fuzzy inference system. Then morphological operation and artificial neural network are applied to remove the halation present. Backpropagation, feedforward, cascaded-feedforward and fitnet artificial neural networks are applied on halation free transmission map for further refinement. Finally, image fusion technique is used to recover an enhanced version of all four images.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Knowledge, awareness and perception towards COVID-19 during early outbreak: a cross-sectional study from southern Pakistan Analysis of Facebook contents of Police Department of Pakistan in the context of Good Governance Perception of Quality about Local Manufacturing of Drugs in Pakistan and Its Qualitative Analysis Frequency of overweight and obesity among Middle School Children A case study of District Hyderabad Pakistan Mineralogical Studies of Manchar Formation (Pliocene), Laki Range, Pakistan: source and Possible Occurrence of Bauxite
×
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