In the current dire situation of the corona virus COVID-19,remote consultations were proposed to avoid cross-infection and regional differences in medical resources.However,the safety of digital medical imaging in rem...In the current dire situation of the corona virus COVID-19,remote consultations were proposed to avoid cross-infection and regional differences in medical resources.However,the safety of digital medical imaging in remote consultations has also attracted more and more attention from the medical industry.To ensure the integrity and security of medical images,this paper proposes a robust watermarking algorithm to authenticate and recover from the distorted medical images based on regions of interest(ROI)and integer wavelet transform(IWT).First,the medical image is divided into two different parts,regions of interest and non-interest regions.Then the integrity of ROI is verified using the hash algorithm,and the recovery data of the ROI region is calculated at the same time.Also,binary images with the basic information of patients are processed by logistic chaotic map encryption,and then the synthetic watermark is embedded in the medical carrier image using IWT transform.The performance of the proposed algorithm is tested by the simulation experiments based on the MATLAB program in CT images of the lungs.Experimental results show that the algorithm can precisely locate the distorted areas of an image and recover the original ROI on the basis of verifying image reliability.The maximum peak signal to noise ratio(PSNR)value of 51.24 has been achieved,which proves that the watermark is invisible and has strong robustness against noise,compression,and filtering attacks.展开更多
As an effective way to securely transfer secret images,secret image sharing(SIS)has been a noteworthy area of research.Basically in a SIS scheme,a secret image is shared via shadows and could be reconstructed by havin...As an effective way to securely transfer secret images,secret image sharing(SIS)has been a noteworthy area of research.Basically in a SIS scheme,a secret image is shared via shadows and could be reconstructed by having the required number of them.A major downside of this method is its noise-like shadows,which draw the malicious users'attention.In order to overcome this problem,SIS schemes with meaningful shadows are introduced in which the shadows are first hidden in innocent-looking cover images and then shared.In most of these schemes,the cover image cannot be recovered without distortion,which makes them useless in case of utilising critical cover images such as military or medical images.Also,embedding the secret data in Least significant bits of the cover image,in many of these schemes,makes them very fragile to steganlysis.A reversible IWT-based SIS scheme using Rook polynomial and Hamming code with authentication is proposed.In order to make the scheme robust to steganalysis,the shadow image is embedded in coefficients of Integer wavelet transform of the cover image.Using Rook polynomial makes the scheme more secure and moreover makes authentication very easy and with no need to share private key to participants.Also,utilising Hamming code lets us embed data with much less required modifications on the cover image which results in high-quality stego images.展开更多
基金This work was supported,in part,by the National Nature Science Foundation of China under grant numbers 61502240,61502096,61304205,61773219in part,by the Natural Science Foundation of Jiangsu Province under grant numbers BK20191401in part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund.
文摘In the current dire situation of the corona virus COVID-19,remote consultations were proposed to avoid cross-infection and regional differences in medical resources.However,the safety of digital medical imaging in remote consultations has also attracted more and more attention from the medical industry.To ensure the integrity and security of medical images,this paper proposes a robust watermarking algorithm to authenticate and recover from the distorted medical images based on regions of interest(ROI)and integer wavelet transform(IWT).First,the medical image is divided into two different parts,regions of interest and non-interest regions.Then the integrity of ROI is verified using the hash algorithm,and the recovery data of the ROI region is calculated at the same time.Also,binary images with the basic information of patients are processed by logistic chaotic map encryption,and then the synthetic watermark is embedded in the medical carrier image using IWT transform.The performance of the proposed algorithm is tested by the simulation experiments based on the MATLAB program in CT images of the lungs.Experimental results show that the algorithm can precisely locate the distorted areas of an image and recover the original ROI on the basis of verifying image reliability.The maximum peak signal to noise ratio(PSNR)value of 51.24 has been achieved,which proves that the watermark is invisible and has strong robustness against noise,compression,and filtering attacks.
基金Iran National Science Foundation,Grant/Award Number:99009224。
文摘As an effective way to securely transfer secret images,secret image sharing(SIS)has been a noteworthy area of research.Basically in a SIS scheme,a secret image is shared via shadows and could be reconstructed by having the required number of them.A major downside of this method is its noise-like shadows,which draw the malicious users'attention.In order to overcome this problem,SIS schemes with meaningful shadows are introduced in which the shadows are first hidden in innocent-looking cover images and then shared.In most of these schemes,the cover image cannot be recovered without distortion,which makes them useless in case of utilising critical cover images such as military or medical images.Also,embedding the secret data in Least significant bits of the cover image,in many of these schemes,makes them very fragile to steganlysis.A reversible IWT-based SIS scheme using Rook polynomial and Hamming code with authentication is proposed.In order to make the scheme robust to steganalysis,the shadow image is embedded in coefficients of Integer wavelet transform of the cover image.Using Rook polynomial makes the scheme more secure and moreover makes authentication very easy and with no need to share private key to participants.Also,utilising Hamming code lets us embed data with much less required modifications on the cover image which results in high-quality stego images.
文摘MRI和CT图像成为医生对于病情诊断的重要方法和手段,在MRI和CT图像中,病变情况等关键信息大都出现在图像的软组织区域中。为了有效保护医学图像软组织区域的信息完整性且不受篡改,提出一种基于整数小波变换域(integer wavelet transform,IWT)的双水印信息隐藏算法。算法首先针对MRI和CT图像的前景区域在图像中存在空间和灰度连续的特征,采用最大类间方差法提取较为粗糙的前景区域,然后根据软组织区域的不同特性提出基于区域统计实质分割,从而获取较为精确的图像实质区域。再次,对精确的实质分割区域提出基于隶属度的拟合方法,利用该方法可得到块状的拟合实质区域,将该区域作为水印嵌入区域。最后对拟合后的实质区域块进行整数小波变换,得到小波高频子带和低频子带。针对中高频子带,采用改进的多比特位直方图平移算法实现可逆水印的嵌入用于MRI和CT图像的版权保护。针对低频子带,使用增强奇异值分解值的第一范数作为零水印,检验图像是否遭到篡改。实验表明将该算法应用于脑部和肺部图像时,嵌有水印的脑部和肺部MRI和CT图像PSNR在50 d B左右,在图像不受攻击时,利用可逆水印可完全复原图像,图像在遭遇粘贴攻击、类似图像篡改攻击等攻击时均能利用零水印准确定位攻击位置,在未攻击区域能准确提取版权信息。
