In addition, most medical watermarking algorithms are aimed at grayscale images therefore, a smaller number of color medical image watermarking algorithms are available. Since traditional embedded watermarking technology degrades the quality of the original images, it is not suitable for medical images. With the increasingly widespread use of medical images in medical institutions and networks, the copyright protection of medical images has become increasingly urgent. Both optical experiments and numerical simulations validate the feasibility of the proposed method. The measurement matrix composes a secret key, and only with this key can authorized users decrypt and reconstruct the original watermark image.

SVDGI provides a new reconstruction method in ghost imaging (GI) by modifying the measurement matrix with the help of singular value decomposition, which carries out the reconstruction process in less time and at higher quality. The proposed watermarking algorithm has good imperceptibility and robustness, and no original host image is needed when extracting the watermark. The watermark image is first encrypted by an SVDGI system, then the encrypted watermark is embedded in the host image with the help of the watermark algorithm, which uses the block discrete cosine transform (DCT) and integer lifting wavelet transform (LWT). The reduction of bit-error rate with respect to the conventional detection method reached up to 100%.Īn optical image watermarking method based on singular value decomposition ghost imaging (SVDGI) and a blind watermarking algorithm is proposed. Both geometric and signal processing attacks were used in the validation of their method. To reinforce the security of their scheme, the watermark was initially shuffled, which prevents any unauthorised detection attempt. At the extraction phase, the suitable detection model was identified by means of a reference message. Then, based on quantisation embedding rules, they generated an accommodative detection model for each attack. To overcome these problems, the authors relied on a diversification technique, which allowed to enlarge and vary the samples. However, the available solutions were not effective, whereas the reference message cannot describe the channel alteration due to a shortage of samples, and the complexity of attacks modelling. They used a reference message to define the parameters of the channel model after the attack. To maintain a good quality, many authors focused on improving the extraction, rather than playing on the embedding parameters. However, after the attack, the distribution of the hosts does not remain the same, resulting in a failure to map coefficients to their correct bits. In quantisation index modulation-based watermarking methods, each host coefficient is replaced by an adequate quantiser according to the embedded bit.

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