{"title":"一种新的基于ct的基于位置尺度分布的乘性图像水印统计检测器","authors":"Sadegh Etemad, M. Amirmazlaghani","doi":"10.1109/IKT.2017.8258636","DOIUrl":null,"url":null,"abstract":"In this study, a new statistical multiplicative watermark detector in contourlet domain is presented. The contourlet coefficients of images are highly non-Gaussian and a proper distribution to model the statistics of the contourlet coefficients is a heavy-tail Probability Distribution Function (PDF). In this study, a multiplicative watermarking scheme is proposed in the contourlet domain using t location-scale distribution (tLS). Afterward, we used the likelihood ratio decision rule and tLS distribution to design an optimal multiplicative watermark detector. The detector showed higher efficiency than other watermarking schemes in the literature, based on the experimental results, and its robustness against different attacks was verified.","PeriodicalId":338914,"journal":{"name":"2017 9th International Conference on Information and Knowledge Technology (IKT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A new statistical detector for CT-based multiplicative image watermarking using the t location-scale distribution\",\"authors\":\"Sadegh Etemad, M. Amirmazlaghani\",\"doi\":\"10.1109/IKT.2017.8258636\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, a new statistical multiplicative watermark detector in contourlet domain is presented. The contourlet coefficients of images are highly non-Gaussian and a proper distribution to model the statistics of the contourlet coefficients is a heavy-tail Probability Distribution Function (PDF). In this study, a multiplicative watermarking scheme is proposed in the contourlet domain using t location-scale distribution (tLS). Afterward, we used the likelihood ratio decision rule and tLS distribution to design an optimal multiplicative watermark detector. The detector showed higher efficiency than other watermarking schemes in the literature, based on the experimental results, and its robustness against different attacks was verified.\",\"PeriodicalId\":338914,\"journal\":{\"name\":\"2017 9th International Conference on Information and Knowledge Technology (IKT)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 9th International Conference on Information and Knowledge Technology (IKT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IKT.2017.8258636\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 9th International Conference on Information and Knowledge Technology (IKT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IKT.2017.8258636","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new statistical detector for CT-based multiplicative image watermarking using the t location-scale distribution
In this study, a new statistical multiplicative watermark detector in contourlet domain is presented. The contourlet coefficients of images are highly non-Gaussian and a proper distribution to model the statistics of the contourlet coefficients is a heavy-tail Probability Distribution Function (PDF). In this study, a multiplicative watermarking scheme is proposed in the contourlet domain using t location-scale distribution (tLS). Afterward, we used the likelihood ratio decision rule and tLS distribution to design an optimal multiplicative watermark detector. The detector showed higher efficiency than other watermarking schemes in the literature, based on the experimental results, and its robustness against different attacks was verified.