{"title":"视频防抖中的失真识别技术","authors":"Yan Liu, MouYan Zou","doi":"10.1109/ICCE.2009.5012178","DOIUrl":null,"url":null,"abstract":"For non-stationary displacement sequence of the real-world image sequence, this paper presents a distortion identification technique based on Hilbert Huang Transform (HHT) to identify the distortion model and distortion frequency of the displacement sequence. Experiment results show that this technique can identify the distortion model and distortion frequency of the displacement sequence accurately and quickly. Based on these identification results, we can realize the video stabilization effectively.","PeriodicalId":154986,"journal":{"name":"2009 Digest of Technical Papers International Conference on Consumer Electronics","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Distortion identification technique in video stabilization\",\"authors\":\"Yan Liu, MouYan Zou\",\"doi\":\"10.1109/ICCE.2009.5012178\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For non-stationary displacement sequence of the real-world image sequence, this paper presents a distortion identification technique based on Hilbert Huang Transform (HHT) to identify the distortion model and distortion frequency of the displacement sequence. Experiment results show that this technique can identify the distortion model and distortion frequency of the displacement sequence accurately and quickly. Based on these identification results, we can realize the video stabilization effectively.\",\"PeriodicalId\":154986,\"journal\":{\"name\":\"2009 Digest of Technical Papers International Conference on Consumer Electronics\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Digest of Technical Papers International Conference on Consumer Electronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCE.2009.5012178\",\"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 Digest of Technical Papers International Conference on Consumer Electronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE.2009.5012178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distortion identification technique in video stabilization
For non-stationary displacement sequence of the real-world image sequence, this paper presents a distortion identification technique based on Hilbert Huang Transform (HHT) to identify the distortion model and distortion frequency of the displacement sequence. Experiment results show that this technique can identify the distortion model and distortion frequency of the displacement sequence accurately and quickly. Based on these identification results, we can realize the video stabilization effectively.