基于图像统计量的非局部图像去噪算法

Lei Wang, Xue-qing Li
{"title":"基于图像统计量的非局部图像去噪算法","authors":"Lei Wang, Xue-qing Li","doi":"10.1109/PIC.2010.5687885","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a robust and image denoising method based on image statistic analysis. The image statistic method based on Weibull distribution is applied to image patch content analysis. According to the content analysis, image patches are classified into three types: smooth type, edge type and texture type. And then, different patch similarity measure method and measure window size are applied to denoise images with different types of patches. Based on the results from various different images, our content based NL-means algorithm is shown to have better performance in both PSNR and visual quality compared to the traditional NL-mean algorithm.","PeriodicalId":142910,"journal":{"name":"2010 IEEE International Conference on Progress in Informatics and Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nonlocal image denoising algorithm based on image statistic\",\"authors\":\"Lei Wang, Xue-qing Li\",\"doi\":\"10.1109/PIC.2010.5687885\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a robust and image denoising method based on image statistic analysis. The image statistic method based on Weibull distribution is applied to image patch content analysis. According to the content analysis, image patches are classified into three types: smooth type, edge type and texture type. And then, different patch similarity measure method and measure window size are applied to denoise images with different types of patches. Based on the results from various different images, our content based NL-means algorithm is shown to have better performance in both PSNR and visual quality compared to the traditional NL-mean algorithm.\",\"PeriodicalId\":142910,\"journal\":{\"name\":\"2010 IEEE International Conference on Progress in Informatics and Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Progress in Informatics and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PIC.2010.5687885\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Progress in Informatics and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIC.2010.5687885","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

本文提出了一种基于图像统计分析的鲁棒图像去噪方法。将基于威布尔分布的图像统计方法应用于图像斑块内容分析。根据内容分析,将图像斑块分为光滑型、边缘型和纹理型三种类型。然后,采用不同的patch相似度度量方法和度量窗口大小对不同类型patch的图像进行去噪。基于各种不同图像的结果,我们的基于内容的NL-means算法在PSNR和视觉质量方面都比传统的NL-mean算法有更好的表现。
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
Nonlocal image denoising algorithm based on image statistic
In this paper, we propose a robust and image denoising method based on image statistic analysis. The image statistic method based on Weibull distribution is applied to image patch content analysis. According to the content analysis, image patches are classified into three types: smooth type, edge type and texture type. And then, different patch similarity measure method and measure window size are applied to denoise images with different types of patches. Based on the results from various different images, our content based NL-means algorithm is shown to have better performance in both PSNR and visual quality compared to the traditional NL-mean algorithm.
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
Data compression of multispectral images for FY-2C geostationary meteorological satellite Redundant De Bruijn graph based location and routing for large-scale peer-to-peer system Content semantic filter based on Domain Ontology An isolated word recognition system based on DSP and improved dynamic time warping algorithm Research on Logistics Carbon Footprint Analysis System
×
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