{"title":"基于cuda的并行化彩色DCT水印算法","authors":"A. Mohammadabadi, A. Chalechale","doi":"10.1109/ICCKE.2016.7802123","DOIUrl":null,"url":null,"abstract":"Image watermarking in DCT domain has a high computational complexity especially for color and high resolution images, where usage of them has been significantly grown. To address this issue, in this article, a data-parallel color DCT watermarking approach is proposed and implemented on GPU using CUDA. Also, in this work, before embedding, the color watermark is compressed using a modified method to get less distortion. CUDA implementation of 8×8 DCT offers 12×-43× speedup with GT 540M and 94×-105× speedup with GTX 580, for different image sizes. In case of embedding procedure, the speedup obtained by GT 540M is between 7× and 26×, and the speedup obtained by GTX 580 is between 46× and 73×, for various case studies. Furthermore, in case of extracting procedure, GT 540M leads to a speedup between 10× and 29×, and GTX 580 leads to a speedup between 75× and 80×, for various case studies.","PeriodicalId":205768,"journal":{"name":"2016 6th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Parallelization of a color DCT watermarking algorithm using a CUDA-based approach\",\"authors\":\"A. Mohammadabadi, A. Chalechale\",\"doi\":\"10.1109/ICCKE.2016.7802123\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image watermarking in DCT domain has a high computational complexity especially for color and high resolution images, where usage of them has been significantly grown. To address this issue, in this article, a data-parallel color DCT watermarking approach is proposed and implemented on GPU using CUDA. Also, in this work, before embedding, the color watermark is compressed using a modified method to get less distortion. CUDA implementation of 8×8 DCT offers 12×-43× speedup with GT 540M and 94×-105× speedup with GTX 580, for different image sizes. In case of embedding procedure, the speedup obtained by GT 540M is between 7× and 26×, and the speedup obtained by GTX 580 is between 46× and 73×, for various case studies. Furthermore, in case of extracting procedure, GT 540M leads to a speedup between 10× and 29×, and GTX 580 leads to a speedup between 75× and 80×, for various case studies.\",\"PeriodicalId\":205768,\"journal\":{\"name\":\"2016 6th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 6th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCKE.2016.7802123\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 6th International Conference on Computer and Knowledge Engineering (ICCKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCKE.2016.7802123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parallelization of a color DCT watermarking algorithm using a CUDA-based approach
Image watermarking in DCT domain has a high computational complexity especially for color and high resolution images, where usage of them has been significantly grown. To address this issue, in this article, a data-parallel color DCT watermarking approach is proposed and implemented on GPU using CUDA. Also, in this work, before embedding, the color watermark is compressed using a modified method to get less distortion. CUDA implementation of 8×8 DCT offers 12×-43× speedup with GT 540M and 94×-105× speedup with GTX 580, for different image sizes. In case of embedding procedure, the speedup obtained by GT 540M is between 7× and 26×, and the speedup obtained by GTX 580 is between 46× and 73×, for various case studies. Furthermore, in case of extracting procedure, GT 540M leads to a speedup between 10× and 29×, and GTX 580 leads to a speedup between 75× and 80×, for various case studies.