{"title":"基于NSCT和融合的中间视图合成新方法","authors":"Fangfang Li, Jifeng Sun","doi":"10.1109/ICSPS.2010.5555471","DOIUrl":null,"url":null,"abstract":"NSCT (Non-Subsampled Contourlet Transform) is widely used in image fusion according to its multiscale, multiorientation and translation invariance. In this paper, a new intermediate view synthesis approach for free viewpoint video based on NSCT and image fusion is proposed. SIFT descriptor is used to detect the distinctive features as matching points of the given images. Then homography matrix is calculated by the matching points, so that the given images can be wrapped to the middle position, and transformed into NSCT domain to fuse, then we fill the holes by blending neighboring colors, the image generated is the intermediate view. The experimental results show that the viability of the proposed method is good.","PeriodicalId":234084,"journal":{"name":"2010 2nd International Conference on Signal Processing Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new approach for intermediate view synthesis based on NSCT and fusion\",\"authors\":\"Fangfang Li, Jifeng Sun\",\"doi\":\"10.1109/ICSPS.2010.5555471\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"NSCT (Non-Subsampled Contourlet Transform) is widely used in image fusion according to its multiscale, multiorientation and translation invariance. In this paper, a new intermediate view synthesis approach for free viewpoint video based on NSCT and image fusion is proposed. SIFT descriptor is used to detect the distinctive features as matching points of the given images. Then homography matrix is calculated by the matching points, so that the given images can be wrapped to the middle position, and transformed into NSCT domain to fuse, then we fill the holes by blending neighboring colors, the image generated is the intermediate view. The experimental results show that the viability of the proposed method is good.\",\"PeriodicalId\":234084,\"journal\":{\"name\":\"2010 2nd International Conference on Signal Processing Systems\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 2nd International Conference on Signal Processing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSPS.2010.5555471\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Conference on Signal Processing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPS.2010.5555471","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new approach for intermediate view synthesis based on NSCT and fusion
NSCT (Non-Subsampled Contourlet Transform) is widely used in image fusion according to its multiscale, multiorientation and translation invariance. In this paper, a new intermediate view synthesis approach for free viewpoint video based on NSCT and image fusion is proposed. SIFT descriptor is used to detect the distinctive features as matching points of the given images. Then homography matrix is calculated by the matching points, so that the given images can be wrapped to the middle position, and transformed into NSCT domain to fuse, then we fill the holes by blending neighboring colors, the image generated is the intermediate view. The experimental results show that the viability of the proposed method is good.