{"title":"小结构的分段梯度先验和保持对比度的图像平滑","authors":"Tingting Li , Fang Li , Huiqing Qi","doi":"10.1016/j.amc.2025.129557","DOIUrl":null,"url":null,"abstract":"<div><div>Image smoothing is a fundamental task in digital image processing with broad applications. However, traditional texture smoothing techniques often result in the loss or blurring of small structural information and contrast. In this paper, we introduce a piecewise gradient prior aimed at overcoming this drawback. The prior is based on a four-segment piecewise (FSP) penalty function, which can process signals at different scales. We also present an effective iterative algorithm based on the alternate direction method of multipliers framework and provide theoretical proof of global convergence for the proposed algorithm. Our method has shown promising results in various applications, including texture removal, clip art compression artifact removal, and edge detection. Experimental results demonstrate the effectiveness and superior performance of our approach in these applications.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":"507 ","pages":"Article 129557"},"PeriodicalIF":3.4000,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A piecewise gradient prior for small structures and contrast preserving image smoothing\",\"authors\":\"Tingting Li , Fang Li , Huiqing Qi\",\"doi\":\"10.1016/j.amc.2025.129557\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Image smoothing is a fundamental task in digital image processing with broad applications. However, traditional texture smoothing techniques often result in the loss or blurring of small structural information and contrast. In this paper, we introduce a piecewise gradient prior aimed at overcoming this drawback. The prior is based on a four-segment piecewise (FSP) penalty function, which can process signals at different scales. We also present an effective iterative algorithm based on the alternate direction method of multipliers framework and provide theoretical proof of global convergence for the proposed algorithm. Our method has shown promising results in various applications, including texture removal, clip art compression artifact removal, and edge detection. Experimental results demonstrate the effectiveness and superior performance of our approach in these applications.</div></div>\",\"PeriodicalId\":55496,\"journal\":{\"name\":\"Applied Mathematics and Computation\",\"volume\":\"507 \",\"pages\":\"Article 129557\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2025-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Mathematics and Computation\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0096300325002838\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematics and Computation","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0096300325002838","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
A piecewise gradient prior for small structures and contrast preserving image smoothing
Image smoothing is a fundamental task in digital image processing with broad applications. However, traditional texture smoothing techniques often result in the loss or blurring of small structural information and contrast. In this paper, we introduce a piecewise gradient prior aimed at overcoming this drawback. The prior is based on a four-segment piecewise (FSP) penalty function, which can process signals at different scales. We also present an effective iterative algorithm based on the alternate direction method of multipliers framework and provide theoretical proof of global convergence for the proposed algorithm. Our method has shown promising results in various applications, including texture removal, clip art compression artifact removal, and edge detection. Experimental results demonstrate the effectiveness and superior performance of our approach in these applications.
期刊介绍:
Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results.
In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.