增强图像平滑度的可逆信息隐藏方案

随着互联网技术的发展和社交网络的普及，可逆信息隐藏技术因其具有无损恢复载体信息的特性而被广泛应用于医疗、军事等领域的隐蔽信息传输。传统的可逆信息隐藏方案大多聚焦于嵌入容量提升和载密图像失真率降低，并未过多关注人们对图像视觉细节的要求，难以抵抗隐藏信息检测方法。针对上述挑战，从增强图像视觉平滑度方面入手，提出了一种增强图像平滑度的可逆信息隐藏方案，在嵌入隐蔽信息的同时提升载密图像最终的视觉质量。具体来说，所提方案将目标图像分为参考区域与非参考区域，利用非参考区域的图像像素预测值与原始像素值的差值作为信息嵌入的判断依据，通过差值平移来嵌入信息；进而构造图像平滑机制，采用高斯滤波作为秘密信息嵌入时像素值修改的模板，对预测值进行滤波计算，将滤波差值无损地加入载体图像中，以达到图像平滑的效果；同时将参考区域的像素值作为边信息，用于实现信息提取方对原始载体图像和秘密信息的无损恢复和提取；并以高斯函数中的滤波系数作为预置秘密信息对嵌入信息进行加密处理以保证嵌入信息的机密性。大量经典图像数据集的测试与分析结果表明，所提方案处理过的载密图像视觉平滑度得到了显著增强，具有较低的失真率、较高的嵌入率和较高的嵌入提取效率。在典型环境下，其生成的载密图像与高斯滤波后的图像相似度可达0.996 3，且可获得37.346的峰值信噪比和0.328 9的嵌入容量。

Reversible data hiding scheme based on enhanced image smoothness

With the prosperity of Internet technology and the popularity of social networks, reversible data hiding technology has been widely adopted in concealed information transmission of medical and military fields with its advantages on secret information recovery.Traditional reversible data hiding schemes mainly focus on the enhancement of embedding capacity and the reduction of the distortion rate of stego image, but pay less attention to the understanding of image details with the human eyes.Thus, it is difficult to resist hidden information detection methods.To solve the above challenge, a reversible data hiding algorithm was proposed, which ensured the visual quality of the stego image in the process of data hiding through the image visual smoothness enhancement.Specifically, the original image was divided into reference area and non-reference area.The secret data was embedded through the translation of the difference, which was calculated according to the predicted pixel value and the original pixel value of the non-reference area.To guarantee the visual quality of the image, smoothing mechanism was constructed, in which a Gaussian filter was utilized as a template to filter the predicted value and to add the filter difference into the cover image without loss.The pixel value of the reference region was used as edge information for lossless restoration of the original image.The filtering coefficient in Gaussian function was exploited as the embedded key to ensure the security of secret information.Simulation results regarding a large number of classical image data sets illustrated that the visual smoothness of stego image processed by this scheme was effectively enhanced with lower distortion rate, higher embedding rate, and higher embedding and extraction efficiency.In a typical circumstance, the similarity between the generated stego image and the Gaussian filter image can reach 0.9963.The PSNR and the embedded capacity can be up to 37.346 and 0.3289 BPP, respectively.