{"title":"一种新的最优检测音频水印方法","authors":"Ivana Milas, Bozidarka Radovic, Danilo Jankovic","doi":"10.1109/MECO.2016.7525717","DOIUrl":null,"url":null,"abstract":"A new audio watermarking algorithm based on Discrete Cosine Transformation (DCT) domain is presented. Watermark embedding procedure relies on probability density function (pdf) modeling. The proposed method ensures optimal detection for weak watermarks even when they are exposed to some common attacks such as noise addition and compression. The performance of this technique is evaluated in terms of Signal to Noise Ratio (SNR).","PeriodicalId":253666,"journal":{"name":"2016 5th Mediterranean Conference on Embedded Computing (MECO)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A new audio watermarking method with optimal detection\",\"authors\":\"Ivana Milas, Bozidarka Radovic, Danilo Jankovic\",\"doi\":\"10.1109/MECO.2016.7525717\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new audio watermarking algorithm based on Discrete Cosine Transformation (DCT) domain is presented. Watermark embedding procedure relies on probability density function (pdf) modeling. The proposed method ensures optimal detection for weak watermarks even when they are exposed to some common attacks such as noise addition and compression. The performance of this technique is evaluated in terms of Signal to Noise Ratio (SNR).\",\"PeriodicalId\":253666,\"journal\":{\"name\":\"2016 5th Mediterranean Conference on Embedded Computing (MECO)\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 5th Mediterranean Conference on Embedded Computing (MECO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MECO.2016.7525717\",\"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 5th Mediterranean Conference on Embedded Computing (MECO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MECO.2016.7525717","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new audio watermarking method with optimal detection
A new audio watermarking algorithm based on Discrete Cosine Transformation (DCT) domain is presented. Watermark embedding procedure relies on probability density function (pdf) modeling. The proposed method ensures optimal detection for weak watermarks even when they are exposed to some common attacks such as noise addition and compression. The performance of this technique is evaluated in terms of Signal to Noise Ratio (SNR).