{"title":"基于压缩感知的PWLCM图像加密","authors":"Omkar Abhishek, S. N. George, P. Deepthi","doi":"10.1109/RAICS.2013.6745445","DOIUrl":null,"url":null,"abstract":"In this paper, compressive sensing is combined with a chaotic key based generation of measurement matrix to provide an effective encryption algorithm for multimedia security. Block-based compressive sensing provides a better way in the field of image and video transmission by reducing the memory requirements and complexity, where as multiple hypothesis prediction provides a competent way in improving PSNR during reconstruction of block based compressive sensed images and videos. The measurement matrix Φ place a crucial role in this compressive sensing and as well as in the reconstruction process. A possibility to generate secure measurement matrix using piecewise linear chaotic map (PWLCM) as the seed and then hiding initial condition, system parameter, number of iterations of PWLCM as the key enable the sender to incorporate room for encryption along with the compression in a single step. The above mentioned scheme provides high level of data security, reduced complexity, compression with a good reconstruction quality and beside all it reduce the burden of sending the measurement matrix along with the data which further reduces the complexity in over all compressive sensing framework.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"PWLCM based image encryption through compressive sensing\",\"authors\":\"Omkar Abhishek, S. N. George, P. Deepthi\",\"doi\":\"10.1109/RAICS.2013.6745445\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, compressive sensing is combined with a chaotic key based generation of measurement matrix to provide an effective encryption algorithm for multimedia security. Block-based compressive sensing provides a better way in the field of image and video transmission by reducing the memory requirements and complexity, where as multiple hypothesis prediction provides a competent way in improving PSNR during reconstruction of block based compressive sensed images and videos. The measurement matrix Φ place a crucial role in this compressive sensing and as well as in the reconstruction process. A possibility to generate secure measurement matrix using piecewise linear chaotic map (PWLCM) as the seed and then hiding initial condition, system parameter, number of iterations of PWLCM as the key enable the sender to incorporate room for encryption along with the compression in a single step. The above mentioned scheme provides high level of data security, reduced complexity, compression with a good reconstruction quality and beside all it reduce the burden of sending the measurement matrix along with the data which further reduces the complexity in over all compressive sensing framework.\",\"PeriodicalId\":184155,\"journal\":{\"name\":\"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RAICS.2013.6745445\",\"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 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RAICS.2013.6745445","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PWLCM based image encryption through compressive sensing
In this paper, compressive sensing is combined with a chaotic key based generation of measurement matrix to provide an effective encryption algorithm for multimedia security. Block-based compressive sensing provides a better way in the field of image and video transmission by reducing the memory requirements and complexity, where as multiple hypothesis prediction provides a competent way in improving PSNR during reconstruction of block based compressive sensed images and videos. The measurement matrix Φ place a crucial role in this compressive sensing and as well as in the reconstruction process. A possibility to generate secure measurement matrix using piecewise linear chaotic map (PWLCM) as the seed and then hiding initial condition, system parameter, number of iterations of PWLCM as the key enable the sender to incorporate room for encryption along with the compression in a single step. The above mentioned scheme provides high level of data security, reduced complexity, compression with a good reconstruction quality and beside all it reduce the burden of sending the measurement matrix along with the data which further reduces the complexity in over all compressive sensing framework.