{"title":"基于子采样和压缩感知的数据隐藏","authors":"Wei Li, Jeng-Shyang Pan, Lijun Yan, Chun-Sheng Yang, Hsiang-Cheh Huang","doi":"10.1109/IIH-MSP.2013.157","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel scheme that considers the data hiding with sub sampling and compressive sensing. We utilize the characteristics of compressive sensing, sparsity and random projection, to embed secret data in the observation domain of the sparse image obtained through compressive sensing. The high bit correction rate (BCR) in experiments shows the high accuracy of our proposed method.","PeriodicalId":105427,"journal":{"name":"2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Data Hiding Based on Subsampling and Compressive Sensing\",\"authors\":\"Wei Li, Jeng-Shyang Pan, Lijun Yan, Chun-Sheng Yang, Hsiang-Cheh Huang\",\"doi\":\"10.1109/IIH-MSP.2013.157\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a novel scheme that considers the data hiding with sub sampling and compressive sensing. We utilize the characteristics of compressive sensing, sparsity and random projection, to embed secret data in the observation domain of the sparse image obtained through compressive sensing. The high bit correction rate (BCR) in experiments shows the high accuracy of our proposed method.\",\"PeriodicalId\":105427,\"journal\":{\"name\":\"2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IIH-MSP.2013.157\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIH-MSP.2013.157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data Hiding Based on Subsampling and Compressive Sensing
This paper proposes a novel scheme that considers the data hiding with sub sampling and compressive sensing. We utilize the characteristics of compressive sensing, sparsity and random projection, to embed secret data in the observation domain of the sparse image obtained through compressive sensing. The high bit correction rate (BCR) in experiments shows the high accuracy of our proposed method.