{"title":"Fast Image Inpainting for DIBR View Synthesis Using Distance Transform and Gaussian Filtering","authors":"E. Dumic, A. Bjelopera, Tina Pogac","doi":"10.54941/ahfe1001125","DOIUrl":null,"url":null,"abstract":"This paper presents a fast and lightweight image inpainting method using distance transform and Gaussian lowpass filtering on disoccluded regions for virtual view synthesis. Virtual views are created from one texture-plus-depth image and afterwards a described method is used for the hole filling process. Proposed algorithm is compared with several state-of-the-art image inpainting methods using different no-reference image quality measures (BRISQUE, NIQE, PIQE). Results for the proposed method show competitive performance, while having lower execution time, concluding that the proposed method can be used in different real-time scenarios.","PeriodicalId":116806,"journal":{"name":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Systems Engineering and Design (IHSED2021) Future Trends and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54941/ahfe1001125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a fast and lightweight image inpainting method using distance transform and Gaussian lowpass filtering on disoccluded regions for virtual view synthesis. Virtual views are created from one texture-plus-depth image and afterwards a described method is used for the hole filling process. Proposed algorithm is compared with several state-of-the-art image inpainting methods using different no-reference image quality measures (BRISQUE, NIQE, PIQE). Results for the proposed method show competitive performance, while having lower execution time, concluding that the proposed method can be used in different real-time scenarios.