{"title":"多分辨率马赛克","authors":"Chiou-Ting Hsu, Ja-Ling Wu","doi":"10.1109/ICIP.1996.560802","DOIUrl":null,"url":null,"abstract":"Mosaic techniques have been used to combine two or more signals into a new one with an invisible seam, and with as little distortion of each signal as possible. Multiresolution representation is an effective method for analyzing the information content of signals, and it also fits a wide spectrum of visual signal processing and visual communication applications. The wavelet transform is one kind of multiresolution representations, and has found a wide variety of application in many aspects, including signal analysis, image coding, image processing, computer vision and etc. Due to its characteristic of multiresolution signal decomposition, the wavelet transform is used for the image mosaic by choosing the width of the mosaic transition zone proportional to the frequency represented in the band. Both 1-D and 2-D signal mosaics are described, and some factors which affect the mosaics are discussed.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"47","resultStr":"{\"title\":\"Multiresolution mosaic\",\"authors\":\"Chiou-Ting Hsu, Ja-Ling Wu\",\"doi\":\"10.1109/ICIP.1996.560802\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mosaic techniques have been used to combine two or more signals into a new one with an invisible seam, and with as little distortion of each signal as possible. Multiresolution representation is an effective method for analyzing the information content of signals, and it also fits a wide spectrum of visual signal processing and visual communication applications. The wavelet transform is one kind of multiresolution representations, and has found a wide variety of application in many aspects, including signal analysis, image coding, image processing, computer vision and etc. Due to its characteristic of multiresolution signal decomposition, the wavelet transform is used for the image mosaic by choosing the width of the mosaic transition zone proportional to the frequency represented in the band. Both 1-D and 2-D signal mosaics are described, and some factors which affect the mosaics are discussed.\",\"PeriodicalId\":192947,\"journal\":{\"name\":\"Proceedings of 3rd IEEE International Conference on Image Processing\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"47\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 3rd IEEE International Conference on Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.1996.560802\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd IEEE International Conference on Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.1996.560802","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mosaic techniques have been used to combine two or more signals into a new one with an invisible seam, and with as little distortion of each signal as possible. Multiresolution representation is an effective method for analyzing the information content of signals, and it also fits a wide spectrum of visual signal processing and visual communication applications. The wavelet transform is one kind of multiresolution representations, and has found a wide variety of application in many aspects, including signal analysis, image coding, image processing, computer vision and etc. Due to its characteristic of multiresolution signal decomposition, the wavelet transform is used for the image mosaic by choosing the width of the mosaic transition zone proportional to the frequency represented in the band. Both 1-D and 2-D signal mosaics are described, and some factors which affect the mosaics are discussed.