The concept of dual image reversible data hiding（DIRDH） is the technique that can produce two camouflage images after embedding secret data into one original image.Moreover,not only can the secret data be extracted ...The concept of dual image reversible data hiding（DIRDH） is the technique that can produce two camouflage images after embedding secret data into one original image.Moreover,not only can the secret data be extracted from two camouflage images but also the original image can be recovered.To achieve high image quality,Lu et al.＇s method applied least-significant-bit（LSB） matching revisited to DIRDH.In order to further improve the image quality,the proposed method modifies LSB matching revisited rules and applies them to DIRDH.According to the experimental results,the image quality of the proposed method is better than that of Lu et al.＇s method.展开更多
Recently, an edge adaptive image stegano- graphic method based on least significant bit （LSB） matching revisited （EA-LSBMR） has been proposed, which holds good visual quality and proper security under appropriate ...Recently, an edge adaptive image stegano- graphic method based on least significant bit （LSB） matching revisited （EA-LSBMR） has been proposed, which holds good visual quality and proper security under appropriate embedding rates. However, from the extensive experiments to EA-LSBMR, we find that the discrete Fourier transform （DFT） spectrum of pixelpairs differences histogram still reveals the presence of a secret message even in a low embedding rate. To enhance the security, a modified scheme is proposed in this paper, which can defeat the above-mentioned analysis and keep the visual quality better than EA-LSBMR in higher embedding rates. Experimental results using a latest universal steganalysis method have demonstrated the proposed method＇s good performance.展开更多
将隐藏信息检测与图像内容分析相结合是当前提高图像隐写分析性能的一个新方向。与基于图像整体内容的检测方法不同,该文分析了最低有效位(Least Significant Bit LSB)匹配隐写对图像子区域统计特性的影响,提出一种新的联合判决检测方...将隐藏信息检测与图像内容分析相结合是当前提高图像隐写分析性能的一个新方向。与基于图像整体内容的检测方法不同,该文分析了最低有效位(Least Significant Bit LSB)匹配隐写对图像子区域统计特性的影响,提出一种新的联合判决检测方法。首先依据图像内容复杂度将整体图像分割为若干类子区域,其次采用两组不同的滤波器分类提取各子区域像素序列直方图频谱特征,之后用各类子区域特征分别训练Bayes分类器以获得其权重,最后对待测图像的每一个子区域进行分类检测,并将结果加权融合得到最终判决。实验结果表明,该方法对LSB匹配隐写的检测性能优于现有典型方法。展开更多
基金supported by MOST under Grants No.105-2410-H-468-010 and No.105-2221-E-468-019
文摘The concept of dual image reversible data hiding（DIRDH） is the technique that can produce two camouflage images after embedding secret data into one original image.Moreover,not only can the secret data be extracted from two camouflage images but also the original image can be recovered.To achieve high image quality,Lu et al.＇s method applied least-significant-bit（LSB） matching revisited to DIRDH.In order to further improve the image quality,the proposed method modifies LSB matching revisited rules and applies them to DIRDH.According to the experimental results,the image quality of the proposed method is better than that of Lu et al.＇s method.
基金supported in part by the National Science Foundation of China for Distinguished Young Scholars under Grant No. 61025013Sino-Singapore JRP under Grant No. 2010DFA11010+1 种基金National NSF of China under Grant No. 61073159Fundamental Research Funds for the Central Universities under Grant No. 2009JBZ006
文摘Recently, an edge adaptive image stegano- graphic method based on least significant bit （LSB） matching revisited （EA-LSBMR） has been proposed, which holds good visual quality and proper security under appropriate embedding rates. However, from the extensive experiments to EA-LSBMR, we find that the discrete Fourier transform （DFT） spectrum of pixelpairs differences histogram still reveals the presence of a secret message even in a low embedding rate. To enhance the security, a modified scheme is proposed in this paper, which can defeat the above-mentioned analysis and keep the visual quality better than EA-LSBMR in higher embedding rates. Experimental results using a latest universal steganalysis method have demonstrated the proposed method＇s good performance.
文摘将隐藏信息检测与图像内容分析相结合是当前提高图像隐写分析性能的一个新方向。与基于图像整体内容的检测方法不同,该文分析了最低有效位(Least Significant Bit LSB)匹配隐写对图像子区域统计特性的影响,提出一种新的联合判决检测方法。首先依据图像内容复杂度将整体图像分割为若干类子区域,其次采用两组不同的滤波器分类提取各子区域像素序列直方图频谱特征,之后用各类子区域特征分别训练Bayes分类器以获得其权重,最后对待测图像的每一个子区域进行分类检测,并将结果加权融合得到最终判决。实验结果表明,该方法对LSB匹配隐写的检测性能优于现有典型方法。
