{"title":"QIM水印游戏","authors":"A. Goteti, P. Moulin","doi":"10.1109/ICIP.2004.1419398","DOIUrl":null,"url":null,"abstract":"Quantization Index Modulation (QIM) methods are widely used for blind data embedding and watermarking. Given a QIM watermarking code, we ask what is the attacker's noise distribution that maximizes probability of error of the detector. For memoryless attacks, the problem is reduced to a convex programming problem. Next, we derive QIM code parameters that are minmax optimal.","PeriodicalId":184798,"journal":{"name":"2004 International Conference on Image Processing, 2004. ICIP '04.","volume":"574 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"QIM watermarking games\",\"authors\":\"A. Goteti, P. Moulin\",\"doi\":\"10.1109/ICIP.2004.1419398\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quantization Index Modulation (QIM) methods are widely used for blind data embedding and watermarking. Given a QIM watermarking code, we ask what is the attacker's noise distribution that maximizes probability of error of the detector. For memoryless attacks, the problem is reduced to a convex programming problem. Next, we derive QIM code parameters that are minmax optimal.\",\"PeriodicalId\":184798,\"journal\":{\"name\":\"2004 International Conference on Image Processing, 2004. ICIP '04.\",\"volume\":\"574 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2004 International Conference on Image Processing, 2004. ICIP '04.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.2004.1419398\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 International Conference on Image Processing, 2004. ICIP '04.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2004.1419398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantization Index Modulation (QIM) methods are widely used for blind data embedding and watermarking. Given a QIM watermarking code, we ask what is the attacker's noise distribution that maximizes probability of error of the detector. For memoryless attacks, the problem is reduced to a convex programming problem. Next, we derive QIM code parameters that are minmax optimal.
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