A content authentication technique based on JPEG-to-JPEG watermarking is proposed in this paper. In this technique, each 8x8 block in a JPEG compressed image is first processed by entropy decoding, and then the quanti...A content authentication technique based on JPEG-to-JPEG watermarking is proposed in this paper. In this technique, each 8x8 block in a JPEG compressed image is first processed by entropy decoding, and then the quantized discrete cosine transform （DCT） is applied to generate DCT coefficients： one DC coefficient and 63 AC coefficients in frequency coefficients. The DCT AC coefficients are used to form zero planes in which the watermark is embedded by a chaotic map. In this way, the watermark information is embedded into JPEG compressed domain, and the output watermarked image is still a JPEG format. The proposed method is especially applicable to content authentication of JPEG image since the quantized coefficients are modified for embedding the watermark and the chaotic system possesses an important property with the high sensitivity on initial values. Experimental results show that the tamper regions are localized accurately when the watermarked JPEG image is maliciously tampered.展开更多
生成对抗网络常常被用于图像着色、语义合成、风格迁移等图像转换任务,但现阶段图像生成模型的训练往往依赖于大量配对的数据集,且只能实现两个图像域之间的转换。针对以上问题,提出了一种基于生成对抗网络的时尚内容和风格迁移模型(con...生成对抗网络常常被用于图像着色、语义合成、风格迁移等图像转换任务,但现阶段图像生成模型的训练往往依赖于大量配对的数据集,且只能实现两个图像域之间的转换。针对以上问题,提出了一种基于生成对抗网络的时尚内容和风格迁移模型(content and style transfer based on generative adversarial network,CS-GAN)。该模型利用对比学习框架最大化时尚单品与生成图像之间的互信息,可保证在时尚单品结构不变的前提下实现内容迁移;通过层一致性动态卷积方法,针对不同风格图像自适应地学习风格特征,实现时尚单品任意风格迁移,对输入的时尚单品进行内容特征(如颜色、纹理)和风格特征(如莫奈风、立体派)的融合,实现多个图像域的转换。在公开的时尚数据集上进行对比实验和结果分析,该方法与其他主流方法相比,在图像合成质量、Inception score和FID距离评价指标上均有所提升。展开更多
为了提供高质量的流媒体服务,内容发布网络(CDN)利用域名解析系统(DNS),将用户重定向到附近的内容服务器。近年来,域名解析系统的发展,尤其是基于IPAnycast的域名解析系统的兴起(例如,Google Public DNS,Open DNS),必将对CDN网络的内容...为了提供高质量的流媒体服务,内容发布网络(CDN)利用域名解析系统(DNS),将用户重定向到附近的内容服务器。近年来,域名解析系统的发展,尤其是基于IPAnycast的域名解析系统的兴起(例如,Google Public DNS,Open DNS),必将对CDN网络的内容发布机制造成影响。同Web、Email等其它Internet服务相比,流媒体服务对网络资源有较高的要求,DNS对其影响更加明显。本文首先阐明基于IPAnycast的域名解析系统对CDN网络内容发布模型的冲击,然后分析其影响流媒体服务质量的各种因素,最后通过实验来比较当使用不同域名解析服务时CDN网络承载的流媒体的服务质量。展开更多
基金supported by the National Natural Science Foundation of China under Grant No.60702025the Research Fund for the Doctoral Program of Higher Education under Grant No.20070613024Sichuan Youth Science & Technology Foundation under Grant No.07ZQ026-004
文摘A content authentication technique based on JPEG-to-JPEG watermarking is proposed in this paper. In this technique, each 8x8 block in a JPEG compressed image is first processed by entropy decoding, and then the quantized discrete cosine transform （DCT） is applied to generate DCT coefficients： one DC coefficient and 63 AC coefficients in frequency coefficients. The DCT AC coefficients are used to form zero planes in which the watermark is embedded by a chaotic map. In this way, the watermark information is embedded into JPEG compressed domain, and the output watermarked image is still a JPEG format. The proposed method is especially applicable to content authentication of JPEG image since the quantized coefficients are modified for embedding the watermark and the chaotic system possesses an important property with the high sensitivity on initial values. Experimental results show that the tamper regions are localized accurately when the watermarked JPEG image is maliciously tampered.
文摘生成对抗网络常常被用于图像着色、语义合成、风格迁移等图像转换任务,但现阶段图像生成模型的训练往往依赖于大量配对的数据集,且只能实现两个图像域之间的转换。针对以上问题,提出了一种基于生成对抗网络的时尚内容和风格迁移模型(content and style transfer based on generative adversarial network,CS-GAN)。该模型利用对比学习框架最大化时尚单品与生成图像之间的互信息,可保证在时尚单品结构不变的前提下实现内容迁移;通过层一致性动态卷积方法,针对不同风格图像自适应地学习风格特征,实现时尚单品任意风格迁移,对输入的时尚单品进行内容特征(如颜色、纹理)和风格特征(如莫奈风、立体派)的融合,实现多个图像域的转换。在公开的时尚数据集上进行对比实验和结果分析,该方法与其他主流方法相比,在图像合成质量、Inception score和FID距离评价指标上均有所提升。
文摘为了提供高质量的流媒体服务,内容发布网络(CDN)利用域名解析系统(DNS),将用户重定向到附近的内容服务器。近年来,域名解析系统的发展,尤其是基于IPAnycast的域名解析系统的兴起(例如,Google Public DNS,Open DNS),必将对CDN网络的内容发布机制造成影响。同Web、Email等其它Internet服务相比,流媒体服务对网络资源有较高的要求,DNS对其影响更加明显。本文首先阐明基于IPAnycast的域名解析系统对CDN网络内容发布模型的冲击,然后分析其影响流媒体服务质量的各种因素,最后通过实验来比较当使用不同域名解析服务时CDN网络承载的流媒体的服务质量。
