{"title":"基于鲁棒中文提醒定理的鲁棒秘密图像共享","authors":"Xiaohui Jin, Fuyou Miao","doi":"10.1109/CCISP55629.2022.9974309","DOIUrl":null,"url":null,"abstract":"In a $(k,\\ n)$ threshold secret image sharing (SIS) scheme, the original secret image can be reconstructed losslessly by collecting no less than $k$ shadow images without errors. However, during the transmission or storage of the shadow image, if the transmission channel is noisy or the storage medium is unreliable, the shadow images will be erroneous. In this case, most of the existing SIS schemes cannot reconstruct the secret image. In an effort to cope with the issue, we propose a robust SIS (RSIS) scheme based on the Robust Chinese Remainder Theorem (RCRT), namely RSIS-RCRT, which can realize the reconstruction of the secret image with high quality under a certain error in the shadow image. In addition, a simple and effective Image Correction Method (ICM) is proposed, which improves the quality of the reconstructed image significantly in RSIS-RCRT scheme. Experiments show that the RSIS-RCRT scheme and ICM are effective.","PeriodicalId":431851,"journal":{"name":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust Secret Image Sharing Based on Robust Chinese Reminder Theorem\",\"authors\":\"Xiaohui Jin, Fuyou Miao\",\"doi\":\"10.1109/CCISP55629.2022.9974309\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a $(k,\\\\ n)$ threshold secret image sharing (SIS) scheme, the original secret image can be reconstructed losslessly by collecting no less than $k$ shadow images without errors. However, during the transmission or storage of the shadow image, if the transmission channel is noisy or the storage medium is unreliable, the shadow images will be erroneous. In this case, most of the existing SIS schemes cannot reconstruct the secret image. In an effort to cope with the issue, we propose a robust SIS (RSIS) scheme based on the Robust Chinese Remainder Theorem (RCRT), namely RSIS-RCRT, which can realize the reconstruction of the secret image with high quality under a certain error in the shadow image. In addition, a simple and effective Image Correction Method (ICM) is proposed, which improves the quality of the reconstructed image significantly in RSIS-RCRT scheme. Experiments show that the RSIS-RCRT scheme and ICM are effective.\",\"PeriodicalId\":431851,\"journal\":{\"name\":\"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCISP55629.2022.9974309\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCISP55629.2022.9974309","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
在$(k,\ n)$阈值秘密图像共享(SIS)方案中,通过收集不少于$k$的阴影图像,可以无损地重建原始秘密图像。然而,在阴影图像的传输或存储过程中,如果传输信道有噪声或存储介质不可靠,则会产生错误的阴影图像。在这种情况下,大多数现有的SIS方案都无法重建秘密图像。为了解决这一问题,我们提出了一种基于鲁棒中国剩余定理(robust Chinese residual Theorem, RCRT)的鲁棒SIS (RSIS)方案,即RSIS-RCRT,可以在阴影图像一定误差下实现高质量的秘密图像重建。此外,提出了一种简单有效的图像校正方法(ICM),显著提高了rss - rcrt方案重建图像的质量。实验表明,RSIS-RCRT方案和ICM方案是有效的。
Robust Secret Image Sharing Based on Robust Chinese Reminder Theorem
In a $(k,\ n)$ threshold secret image sharing (SIS) scheme, the original secret image can be reconstructed losslessly by collecting no less than $k$ shadow images without errors. However, during the transmission or storage of the shadow image, if the transmission channel is noisy or the storage medium is unreliable, the shadow images will be erroneous. In this case, most of the existing SIS schemes cannot reconstruct the secret image. In an effort to cope with the issue, we propose a robust SIS (RSIS) scheme based on the Robust Chinese Remainder Theorem (RCRT), namely RSIS-RCRT, which can realize the reconstruction of the secret image with high quality under a certain error in the shadow image. In addition, a simple and effective Image Correction Method (ICM) is proposed, which improves the quality of the reconstructed image significantly in RSIS-RCRT scheme. Experiments show that the RSIS-RCRT scheme and ICM are effective.