基于局部特征的图像增强双向扩散算法

Zhonghua Wang, Faliang Huang, Shijie Hu
{"title":"基于局部特征的图像增强双向扩散算法","authors":"Zhonghua Wang, Faliang Huang, Shijie Hu","doi":"10.1145/3033288.3033338","DOIUrl":null,"url":null,"abstract":"To deal with the problem that the partial differential equation on image enhancement causes the edge blurring, block effect and ringing effect and so on, a new bidirectional diffusion model based on local features, which smooths the flat region and sharpens the edge in image, is presented. According to the edge features, the presented model chooses the different diffusion methods, that is to say, the non-edge is denoised by the forward diffusion in normal direction and the forward diffusion in tangential direction, while the edge is sharpened by the backward diffusion in normal direction and the forward diffusion in tangential direction. Through the simulation experiments, the model can not only better preserve the image feature, but also more obviously improve the defect contrast.","PeriodicalId":253625,"journal":{"name":"International Conference on Network, Communication and Computing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bidirectional Diffusion Algorithm for Image Enhancement with Local Feature\",\"authors\":\"Zhonghua Wang, Faliang Huang, Shijie Hu\",\"doi\":\"10.1145/3033288.3033338\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To deal with the problem that the partial differential equation on image enhancement causes the edge blurring, block effect and ringing effect and so on, a new bidirectional diffusion model based on local features, which smooths the flat region and sharpens the edge in image, is presented. According to the edge features, the presented model chooses the different diffusion methods, that is to say, the non-edge is denoised by the forward diffusion in normal direction and the forward diffusion in tangential direction, while the edge is sharpened by the backward diffusion in normal direction and the forward diffusion in tangential direction. Through the simulation experiments, the model can not only better preserve the image feature, but also more obviously improve the defect contrast.\",\"PeriodicalId\":253625,\"journal\":{\"name\":\"International Conference on Network, Communication and Computing\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Network, Communication and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3033288.3033338\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Network, Communication and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3033288.3033338","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

针对图像增强中的偏微分方程导致图像边缘模糊、块效应和环形效应等问题,提出了一种新的基于局部特征的双向扩散模型,使图像中的平坦区域平滑,边缘锐化。该模型根据边缘特征选择了不同的扩散方法,即通过法向正向扩散和切向正向扩散对非边缘进行去噪,通过法向反向扩散和切向正向扩散对边缘进行锐化。通过仿真实验,该模型既能更好地保留图像特征,又能更明显地提高缺陷对比度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bidirectional Diffusion Algorithm for Image Enhancement with Local Feature
To deal with the problem that the partial differential equation on image enhancement causes the edge blurring, block effect and ringing effect and so on, a new bidirectional diffusion model based on local features, which smooths the flat region and sharpens the edge in image, is presented. According to the edge features, the presented model chooses the different diffusion methods, that is to say, the non-edge is denoised by the forward diffusion in normal direction and the forward diffusion in tangential direction, while the edge is sharpened by the backward diffusion in normal direction and the forward diffusion in tangential direction. Through the simulation experiments, the model can not only better preserve the image feature, but also more obviously improve the defect contrast.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信