{"title":"基于局部小波特征的全景图像拼接","authors":"Feng Guo, Y. Wang","doi":"10.1109/NBiS.2016.47","DOIUrl":null,"url":null,"abstract":"In this paper, an efficient method based on local wavelet-features is proposed for Panoramic Image Mosaics. Wavelet can describe a wide variety of image characteristics and a key component for in image-related applications. For the feature-extraction stage, we exploit wavelet-subband statistics to construct local feature vectors for image-patch representation. Experimental results show that the local wavelet-features are able to produce plausible panoramic images.","PeriodicalId":390397,"journal":{"name":"2016 19th International Conference on Network-Based Information Systems (NBiS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Panoramic Image Mosaics Using Local Wavelet-Features\",\"authors\":\"Feng Guo, Y. Wang\",\"doi\":\"10.1109/NBiS.2016.47\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an efficient method based on local wavelet-features is proposed for Panoramic Image Mosaics. Wavelet can describe a wide variety of image characteristics and a key component for in image-related applications. For the feature-extraction stage, we exploit wavelet-subband statistics to construct local feature vectors for image-patch representation. Experimental results show that the local wavelet-features are able to produce plausible panoramic images.\",\"PeriodicalId\":390397,\"journal\":{\"name\":\"2016 19th International Conference on Network-Based Information Systems (NBiS)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 19th International Conference on Network-Based Information Systems (NBiS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NBiS.2016.47\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 19th International Conference on Network-Based Information Systems (NBiS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NBiS.2016.47","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Panoramic Image Mosaics Using Local Wavelet-Features
In this paper, an efficient method based on local wavelet-features is proposed for Panoramic Image Mosaics. Wavelet can describe a wide variety of image characteristics and a key component for in image-related applications. For the feature-extraction stage, we exploit wavelet-subband statistics to construct local feature vectors for image-patch representation. Experimental results show that the local wavelet-features are able to produce plausible panoramic images.
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