基于最大后验方法的混合噪声边缘检测

IF 1.2 4区数学 Q2 MATHEMATICS, APPLIED

Inverse Problems and Imaging Pub Date : 2021-01-01 DOI:10.3934/IPI.2021035

Yuying Shi, Zi-peng Liu, Xiaoying Wang, Jinping Zhang

{"title":"基于最大后验方法的混合噪声边缘检测","authors":"Yuying Shi, Zi-peng Liu, Xiaoying Wang, Jinping Zhang","doi":"10.3934/IPI.2021035","DOIUrl":null,"url":null,"abstract":"Edge detection is an important problem in image processing, especially for mixed noise. In this work, we propose a variational edge detection model with mixed noise by using Maximum A-Posteriori (MAP) approach. The novel model is formed with the regularization terms and the data fidelity terms that feature different mixed noise. Furthermore, we adopt the alternating direction method of multipliers (ADMM) to solve the proposed model. Numerical experiments on a variety of gray and color images demonstrate the efficiency of the proposed model.","PeriodicalId":50274,"journal":{"name":"Inverse Problems and Imaging","volume":"219 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Edge detection with mixed noise based on maximum a posteriori approach\",\"authors\":\"Yuying Shi, Zi-peng Liu, Xiaoying Wang, Jinping Zhang\",\"doi\":\"10.3934/IPI.2021035\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Edge detection is an important problem in image processing, especially for mixed noise. In this work, we propose a variational edge detection model with mixed noise by using Maximum A-Posteriori (MAP) approach. The novel model is formed with the regularization terms and the data fidelity terms that feature different mixed noise. Furthermore, we adopt the alternating direction method of multipliers (ADMM) to solve the proposed model. Numerical experiments on a variety of gray and color images demonstrate the efficiency of the proposed model.\",\"PeriodicalId\":50274,\"journal\":{\"name\":\"Inverse Problems and Imaging\",\"volume\":\"219 1\",\"pages\":\"\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Inverse Problems and Imaging\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.3934/IPI.2021035\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Inverse Problems and Imaging","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.3934/IPI.2021035","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}

引用次数: 1

摘要

边缘检测是图像处理，特别是混合噪声图像处理中的一个重要问题。在这项工作中，我们提出了一种使用最大a -后验(MAP)方法的混合噪声变分边缘检测模型。该模型由具有不同混合噪声特征的正则化项和数据保真度项组成。此外，我们采用乘法器的交替方向法(ADMM)来求解所提出的模型。在各种灰度和彩色图像上的数值实验证明了该模型的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Edge detection with mixed noise based on maximum a posteriori approach

Edge detection is an important problem in image processing, especially for mixed noise. In this work, we propose a variational edge detection model with mixed noise by using Maximum A-Posteriori (MAP) approach. The novel model is formed with the regularization terms and the data fidelity terms that feature different mixed noise. Furthermore, we adopt the alternating direction method of multipliers (ADMM) to solve the proposed model. Numerical experiments on a variety of gray and color images demonstrate the efficiency of the proposed model.

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

Inverse Problems and Imaging 数学-物理：数学物理

CiteScore

2.50

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Inverse Problems and Imaging publishes research articles of the highest quality that employ innovative mathematical and modeling techniques to study inverse and imaging problems arising in engineering and other sciences. Every published paper has a strong mathematical orientation employing methods from such areas as control theory, discrete mathematics, differential geometry, harmonic analysis, functional analysis, integral geometry, mathematical physics, numerical analysis, optimization, partial differential equations, and stochastic and statistical methods. The field of applications includes medical and other imaging, nondestructive testing, geophysical prospection and remote sensing as well as image analysis and image processing. This journal is committed to recording important new results in its field and will maintain the highest standards of innovation and quality. To be published in this journal, a paper must be correct, novel, nontrivial and of interest to a substantial number of researchers and readers.