{"title":"基于泰勒射流分割的分段式 Affine-Linear 芒福德-沙模型的高效算法","authors":"Lukas Kiefer, Martin Storath, Andreas Weinmann","doi":"10.1109/TIP.2019.2937040","DOIUrl":null,"url":null,"abstract":"<p><p>We propose an algorithm to efficiently compute approximate solutions of the piecewise affine Mumford-Shah model. The algorithm is based on a novel reformulation of the underlying optimization problem in terms of Taylor jets. A splitting approach leads to linewise segmented jet estimation problems for which we propose an exact and efficient solver. The proposed method has the combined advantages of prior algorithms: it directly yields a partition, it does not need an initialization procedure, and it is highly parallelizable. The experiments show that the algorithm has lower computation times and that the solutions often have lower functional values than the state-of-the-art.</p>","PeriodicalId":13217,"journal":{"name":"IEEE Transactions on Image Processing","volume":"29 1","pages":""},"PeriodicalIF":10.8000,"publicationDate":"2019-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Efficient Algorithm for the Piecewise Affine-Linear Mumford-Shah Model Based on a Taylor Jet Splitting.\",\"authors\":\"Lukas Kiefer, Martin Storath, Andreas Weinmann\",\"doi\":\"10.1109/TIP.2019.2937040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We propose an algorithm to efficiently compute approximate solutions of the piecewise affine Mumford-Shah model. The algorithm is based on a novel reformulation of the underlying optimization problem in terms of Taylor jets. A splitting approach leads to linewise segmented jet estimation problems for which we propose an exact and efficient solver. The proposed method has the combined advantages of prior algorithms: it directly yields a partition, it does not need an initialization procedure, and it is highly parallelizable. The experiments show that the algorithm has lower computation times and that the solutions often have lower functional values than the state-of-the-art.</p>\",\"PeriodicalId\":13217,\"journal\":{\"name\":\"IEEE Transactions on Image Processing\",\"volume\":\"29 1\",\"pages\":\"\"},\"PeriodicalIF\":10.8000,\"publicationDate\":\"2019-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Image Processing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1109/TIP.2019.2937040\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Image Processing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/TIP.2019.2937040","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
An Efficient Algorithm for the Piecewise Affine-Linear Mumford-Shah Model Based on a Taylor Jet Splitting.
We propose an algorithm to efficiently compute approximate solutions of the piecewise affine Mumford-Shah model. The algorithm is based on a novel reformulation of the underlying optimization problem in terms of Taylor jets. A splitting approach leads to linewise segmented jet estimation problems for which we propose an exact and efficient solver. The proposed method has the combined advantages of prior algorithms: it directly yields a partition, it does not need an initialization procedure, and it is highly parallelizable. The experiments show that the algorithm has lower computation times and that the solutions often have lower functional values than the state-of-the-art.
期刊介绍:
The IEEE Transactions on Image Processing delves into groundbreaking theories, algorithms, and structures concerning the generation, acquisition, manipulation, transmission, scrutiny, and presentation of images, video, and multidimensional signals across diverse applications. Topics span mathematical, statistical, and perceptual aspects, encompassing modeling, representation, formation, coding, filtering, enhancement, restoration, rendering, halftoning, search, and analysis of images, video, and multidimensional signals. Pertinent applications range from image and video communications to electronic imaging, biomedical imaging, image and video systems, and remote sensing.