{"title":"压缩感知在Huffman编码DWT SVD医学图像水印中的应用","authors":"Irvan Ragil Boesandi, Irma Safitri, E. Suhartono","doi":"10.1109/ICCEREC.2018.8712085","DOIUrl":null,"url":null,"abstract":"In this study, we propose Huffman coding and compressive sensing (CS) for medical image watermarking. The methods used are Huffman coding, CS, discrete wavelet transform (DWT) and singular value decomposition (SVD). Experiment results show that images can be compressed generally above 50% and are lossless at the time of decompression by having the SSIM value of 1. Our system have the best MSE value of 0.23 and the best PSNR value of 56.5 dB.","PeriodicalId":250054,"journal":{"name":"2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Compressive Sensing in the Huffman Coding DWT SVD Medical Image Watermarking\",\"authors\":\"Irvan Ragil Boesandi, Irma Safitri, E. Suhartono\",\"doi\":\"10.1109/ICCEREC.2018.8712085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, we propose Huffman coding and compressive sensing (CS) for medical image watermarking. The methods used are Huffman coding, CS, discrete wavelet transform (DWT) and singular value decomposition (SVD). Experiment results show that images can be compressed generally above 50% and are lossless at the time of decompression by having the SSIM value of 1. Our system have the best MSE value of 0.23 and the best PSNR value of 56.5 dB.\",\"PeriodicalId\":250054,\"journal\":{\"name\":\"2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCEREC.2018.8712085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEREC.2018.8712085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Compressive Sensing in the Huffman Coding DWT SVD Medical Image Watermarking
In this study, we propose Huffman coding and compressive sensing (CS) for medical image watermarking. The methods used are Huffman coding, CS, discrete wavelet transform (DWT) and singular value decomposition (SVD). Experiment results show that images can be compressed generally above 50% and are lossless at the time of decompression by having the SSIM value of 1. Our system have the best MSE value of 0.23 and the best PSNR value of 56.5 dB.
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