A robust blind medical image watermarking approach for telemedicine applications

Abstract

In order to enhance the security of exchanged medical images in telemedicine, we propose in this paper a blind and robust approach for medical image protection. This approach consists in embedding patient information and image acquisition data in the image. This imperceptible integration must generate the least possible distortion. The watermarked image must present the same clinical reading as the original image. The proposed approach is applied in the frequency domain. For this purpose, four transforms were used: discrete wavelets transform, non-subsampled contourlet transform, non-subsampled shearlet transform and discreet cosine transform. All these transforms was combined with Schur decomposition and the watermark bits were integrated in the upper triangular matrix. To obtain a satisfactory compromise between robustness and imperceptibility, the integration was performed in the medium frequencies of the image. Imperceptibility and robustness experimental results shows that the proposed methods maintain a high quality of watermarked images and are remarkably robust against several conventional attacks. Keywords Medical image Á Digital watermarking Á Discrete wavelet transform Á Non-subsampled contourlet transform Á Non-subsampled shearlet transform Á Discreet cosine transform Á Schur decomposition

Blind and Robust Watermarking Scheme in Hybrid Domain for Copyright Protection of Medical Images

“…The comparison shown in Table XXVI and its corresponding bar graph shown in Figure 28. The Results shown in Table XXVI and Figure 28 reveals that our proposed technique outperforms the technique [55].…”

“…Finally we compared the proposed technique with the technique recently reported by Kahlessename et. al [55]. The comparison shown in Table XXVI and its corresponding bar graph shown in Figure 28.…”

A secure lossless recovery for medical images based on image encoding and data self-embedding

“…Recovery of compressed data from high bit plane image (b). Recovery of compressed data from low bit plane image (6) Data refinement between the compressed data produced by two bit plane images After two groups compressed data are derived from Low p and High p , the data refinement between these two groups of data must be conducted to obtain real and effective compressed data.…”

“…As the cloud is regarded as dishonest entity, the privacy protection of outsourced image has drawn much attention from researchers, and many schemes have been proposed to solve the problem. In general, there are two approaches to protect privacy of the outsourced image; one is to conduct encryption of image before it is outsourced to the cloud [1][2][3], the other one is to utilize the combination of encryption and digital watermarking to protect images [4][5][6].…”

An efficient image steganography approach based on QR factorization and singular value decomposition in non‐subsampled contourlet transform domain

“…Data encryption capability is weaker than the usual LSB method since this method embeds data in two layers. Kahlessenane et al 8 proposed a similar work where four types of transform domain—DWT, non‐subsampled contourlet transform (NSCT), nonsubsampled shearlet transform (NSST), and discrete cosine transform (DCT) were combined with Schur decomposition to fabricate the stego image. DWT‐PSNR Schur's value is determined to be superior to the other transforms.…”