{"title":"图像涂抹的非局部曲率驱动扩散模型","authors":"Li Li, Han Yu","doi":"10.1109/IAS.2009.141","DOIUrl":null,"url":null,"abstract":"A nonlocal image inpainting model is proposed by incorporating the nonlocal differential operators into the curvature-driven diffusion model. The new model differs from the original model in that pixels of similar structures rather than pixels in the neighborhood (the case for the original model) are utilized to estimate the lost pixels. This difference makes the new model performs very efficiently in inpainting images, especially textured images.","PeriodicalId":240354,"journal":{"name":"2009 Fifth International Conference on Information Assurance and Security","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Nonlocal Curvature-Driven Diffusion Model for Image Inpainting\",\"authors\":\"Li Li, Han Yu\",\"doi\":\"10.1109/IAS.2009.141\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A nonlocal image inpainting model is proposed by incorporating the nonlocal differential operators into the curvature-driven diffusion model. The new model differs from the original model in that pixels of similar structures rather than pixels in the neighborhood (the case for the original model) are utilized to estimate the lost pixels. This difference makes the new model performs very efficiently in inpainting images, especially textured images.\",\"PeriodicalId\":240354,\"journal\":{\"name\":\"2009 Fifth International Conference on Information Assurance and Security\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-08-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Fifth International Conference on Information Assurance and Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAS.2009.141\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Fifth International Conference on Information Assurance and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAS.2009.141","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Nonlocal Curvature-Driven Diffusion Model for Image Inpainting
A nonlocal image inpainting model is proposed by incorporating the nonlocal differential operators into the curvature-driven diffusion model. The new model differs from the original model in that pixels of similar structures rather than pixels in the neighborhood (the case for the original model) are utilized to estimate the lost pixels. This difference makes the new model performs very efficiently in inpainting images, especially textured images.
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