Edge Guided High Order Image Smoothing

Haoxing Wang, Longquan Dai, Xiaopeng Zhang
{"title":"Edge Guided High Order Image Smoothing","authors":"Haoxing Wang, Longquan Dai, Xiaopeng Zhang","doi":"10.1109/ACPR.2013.47","DOIUrl":null,"url":null,"abstract":"Edge-preserving smoothing has recently emerged as a valuable tool for a variety of applications in computer graphics and image processing. Edge-preserving smoothing using first order smoothness prior in the regularization term under optimization framework tends to bias the smoothing result forward the constant image. Although using high order smoothness prior can alleviate this problem, it tends to obtain the over-smoothed result. In this paper, we present an effective and practical image editing method which can sharply preserve the salient edges and at the same time smooths the continuous regions using high order smoothness prior to achieve the smoothing results different from the first order smoothness prior. Finally, we demonstrate the effectiveness of our method in the context of image denoising, image abstraction and image enhancement.","PeriodicalId":365633,"journal":{"name":"2013 2nd IAPR Asian Conference on Pattern Recognition","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 2nd IAPR Asian Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPR.2013.47","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Edge-preserving smoothing has recently emerged as a valuable tool for a variety of applications in computer graphics and image processing. Edge-preserving smoothing using first order smoothness prior in the regularization term under optimization framework tends to bias the smoothing result forward the constant image. Although using high order smoothness prior can alleviate this problem, it tends to obtain the over-smoothed result. In this paper, we present an effective and practical image editing method which can sharply preserve the salient edges and at the same time smooths the continuous regions using high order smoothness prior to achieve the smoothing results different from the first order smoothness prior. Finally, we demonstrate the effectiveness of our method in the context of image denoising, image abstraction and image enhancement.
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
边缘引导的高阶图像平滑
在计算机图形学和图像处理的各种应用中,边缘保持平滑已成为一种有价值的工具。在优化框架下,在正则化项中使用一阶平滑先验的保边平滑会使平滑结果向常数图像偏移。虽然使用高阶平滑先验可以缓解这一问题,但往往会得到过度平滑的结果。本文提出了一种有效实用的图像编辑方法,该方法在保留显著边缘的同时,利用高阶平滑先验对连续区域进行平滑,从而获得不同于一阶平滑先验的平滑效果。最后,我们在图像去噪、图像抽象和图像增强方面验证了该方法的有效性。
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
Automatic Compensation of Radial Distortion by Minimizing Entropy of Histogram of Oriented Gradients A Robust and Efficient Minutia-Based Fingerprint Matching Algorithm Sclera Recognition - A Survey A Non-local Sparse Model for Intrinsic Images Classification Based on Boolean Algebra and Its Application to the Prediction of Recurrence of Liver Cancer
×
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