Xuan Zhu, Ning Wang, Enbiao Lin, Qiuju Li, Xufeng Zhang
{"title":"结合稀疏表示和全变分的图像分解模型","authors":"Xuan Zhu, Ning Wang, Enbiao Lin, Qiuju Li, Xufeng Zhang","doi":"10.1109/ICINFA.2013.6720275","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new decomposition model combined with sparse representation and total variation (SRTV), which allows us to separate cartoon and texture components from an image. The SRTV model naturally fits into the framework of separation and produces separated layers, meanwhile, denoising and inpainting process appears as the byproducts. Therefore, the new approach incorporates separation, denoising, and inpainting as a unified framework. We demonstrate the performance of the new approach through several examples.","PeriodicalId":250844,"journal":{"name":"2013 IEEE International Conference on Information and Automation (ICIA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Image decomposition model combined with sparse representation and total variation\",\"authors\":\"Xuan Zhu, Ning Wang, Enbiao Lin, Qiuju Li, Xufeng Zhang\",\"doi\":\"10.1109/ICINFA.2013.6720275\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new decomposition model combined with sparse representation and total variation (SRTV), which allows us to separate cartoon and texture components from an image. The SRTV model naturally fits into the framework of separation and produces separated layers, meanwhile, denoising and inpainting process appears as the byproducts. Therefore, the new approach incorporates separation, denoising, and inpainting as a unified framework. We demonstrate the performance of the new approach through several examples.\",\"PeriodicalId\":250844,\"journal\":{\"name\":\"2013 IEEE International Conference on Information and Automation (ICIA)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Information and Automation (ICIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICINFA.2013.6720275\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Information and Automation (ICIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINFA.2013.6720275","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image decomposition model combined with sparse representation and total variation
In this paper, we propose a new decomposition model combined with sparse representation and total variation (SRTV), which allows us to separate cartoon and texture components from an image. The SRTV model naturally fits into the framework of separation and produces separated layers, meanwhile, denoising and inpainting process appears as the byproducts. Therefore, the new approach incorporates separation, denoising, and inpainting as a unified framework. We demonstrate the performance of the new approach through several examples.