{"title":"基于小波的阈值选择水印检测方法的性能","authors":"B. Molavi, H. Ahmadi, A. Sadr","doi":"10.1109/ICEE.2007.4287291","DOIUrl":null,"url":null,"abstract":"Watermark detection can be considered as an estimation problem in which the watermark sequence has to be estimated from a possibly distorted image. In this paper, we use wavelet threshold estimation for extraction of watermark sequence. The correlation matching is then used for checking for the presence of the watermark. It is shown that the performance of this method is superior to that of correlation matching. The performance of two threshold selection methods are compared for this purpose. The watermark embedding is performed in wavelet domain.","PeriodicalId":291800,"journal":{"name":"2007 International Conference on Electrical Engineering","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance of Wavelet - Based Threshold Selection Schemes for Watermark Detection\",\"authors\":\"B. Molavi, H. Ahmadi, A. Sadr\",\"doi\":\"10.1109/ICEE.2007.4287291\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Watermark detection can be considered as an estimation problem in which the watermark sequence has to be estimated from a possibly distorted image. In this paper, we use wavelet threshold estimation for extraction of watermark sequence. The correlation matching is then used for checking for the presence of the watermark. It is shown that the performance of this method is superior to that of correlation matching. The performance of two threshold selection methods are compared for this purpose. The watermark embedding is performed in wavelet domain.\",\"PeriodicalId\":291800,\"journal\":{\"name\":\"2007 International Conference on Electrical Engineering\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEE.2007.4287291\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEE.2007.4287291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance of Wavelet - Based Threshold Selection Schemes for Watermark Detection
Watermark detection can be considered as an estimation problem in which the watermark sequence has to be estimated from a possibly distorted image. In this paper, we use wavelet threshold estimation for extraction of watermark sequence. The correlation matching is then used for checking for the presence of the watermark. It is shown that the performance of this method is superior to that of correlation matching. The performance of two threshold selection methods are compared for this purpose. The watermark embedding is performed in wavelet domain.
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