{"title":"根据图像的四叉树计算图像中的水印容量","authors":"F. Yaghmaee, M. Jamzad","doi":"10.1109/ISSPIT.2005.1577205","DOIUrl":null,"url":null,"abstract":"Determining the capacity of watermark for images is a complex task. This capacity may be influenced by many factors such as the content of image and also the strength of watermark. In some recent works the image content has been considered for calculation of watermark capacity. One such approach is to use the noise visibility function (NVF) introduced in (Voloshynovsky, et al., 1999). In this paper we introduced a new method for finding NVF according to the quad tree representation of image instead of using pixel neighborhood data. Our experimental results showed that the depth of a pixel in image quad tree represents much information about the pixel and its maximum allowable distortion compared to pixel neighborhood data as used by the existing NVF computing method. Our method for determining NVF, gave similar results for image capacity compared to the approach based on original NVF calculation as given in (F. Zhang and H. Zhang, June 2004)","PeriodicalId":421826,"journal":{"name":"Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.","volume":"66 9","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Computing watermark capacity in images according to their quad tree\",\"authors\":\"F. Yaghmaee, M. Jamzad\",\"doi\":\"10.1109/ISSPIT.2005.1577205\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Determining the capacity of watermark for images is a complex task. This capacity may be influenced by many factors such as the content of image and also the strength of watermark. In some recent works the image content has been considered for calculation of watermark capacity. One such approach is to use the noise visibility function (NVF) introduced in (Voloshynovsky, et al., 1999). In this paper we introduced a new method for finding NVF according to the quad tree representation of image instead of using pixel neighborhood data. Our experimental results showed that the depth of a pixel in image quad tree represents much information about the pixel and its maximum allowable distortion compared to pixel neighborhood data as used by the existing NVF computing method. Our method for determining NVF, gave similar results for image capacity compared to the approach based on original NVF calculation as given in (F. Zhang and H. Zhang, June 2004)\",\"PeriodicalId\":421826,\"journal\":{\"name\":\"Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.\",\"volume\":\"66 9\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSPIT.2005.1577205\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT.2005.1577205","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
摘要
确定图像水印的容量是一项复杂的任务。这种能力可能受到图像内容和水印强度等诸多因素的影响。在最近的一些研究中,考虑了图像内容来计算水印容量。其中一种方法是使用(Voloshynovsky, et al., 1999)中引入的噪声可见性函数(NVF)。本文提出了一种利用图像的四叉树表示代替像素邻域数据寻找NVF的新方法。实验结果表明,与现有NVF计算方法中使用的像素邻域数据相比,图像四叉树中像素的深度代表了像素及其最大允许畸变的更多信息。与基于原始NVF计算的方法(F. Zhang and H. Zhang, 2004年6月)相比,我们确定NVF的方法给出了类似的图像容量结果。
Computing watermark capacity in images according to their quad tree
Determining the capacity of watermark for images is a complex task. This capacity may be influenced by many factors such as the content of image and also the strength of watermark. In some recent works the image content has been considered for calculation of watermark capacity. One such approach is to use the noise visibility function (NVF) introduced in (Voloshynovsky, et al., 1999). In this paper we introduced a new method for finding NVF according to the quad tree representation of image instead of using pixel neighborhood data. Our experimental results showed that the depth of a pixel in image quad tree represents much information about the pixel and its maximum allowable distortion compared to pixel neighborhood data as used by the existing NVF computing method. Our method for determining NVF, gave similar results for image capacity compared to the approach based on original NVF calculation as given in (F. Zhang and H. Zhang, June 2004)