A Robust Medical Image Watermarking Scheme Based on Nature-Inspired Optimization for Telemedicine Applications

Abstract

Medical images and patient information are routinely transmitted to a remote radiologist to assist in diagnosis. It is critical in e-healthcare systems to ensure that data are accurately transmitted. Medical images of a person’s body can be used against them in many ways, including by transmitting them. Copyright and intellectual property laws prohibit the unauthorized use of medical images. Digital watermarking is used to prove the authenticity of the medical images before diagnosis. In this paper, we proposed a hybrid watermarking scheme using the Slantlet transform, randomized-singular value decomposition, and optimization techniques inspired by nature (Firefly algorithm). The watermark image is encrypted using the XOR encryption technique. Extensive testing reveals that our innovative approach outperforms the existing methods based on the NC, SSIM, and PSNR. The SSIM and NC values of watermarked image and extracted watermark are close to or equal to 1 at a scaling factor of 0.06, and the PSNR of the proposed scheme lies between 58 dB and 59 dB, which shows the better performance of the scheme.

Robust Medical Image Watermarking Scheme Using PSO, LWT, and Hessenberg Decomposition

“…The findings indicate that the envisaged system exhibited satisfactory performance, even in the presence of a filtering attack. Furthermore, upon conducting a comparative analysis of the outcomes with other extant methodologies, namely [28,[30][31][32], at intensities of 0.05, 0.025, and 0.10 (as presented in Table 5), it was noted that the findings of [31,32] bear similarity to the suggested approach at an intensity of 0.050. At the intensity of 0.025 and 0.010, the performance of our approach is much better than other similar schemes.…”

“…The obtained results demonstrate that, when exposed to a JPEG compression attack, the proposed approach performed better than expected. Furthermore, upon conducting a comparative analysis of the outcomes with other pre-existing methodologies, namely [28,[30][31][32], concerning quality factors 80 and 90 (as presented in Table 3), it was observed that the outcomes of [28,32] exhibit a resemblance to the proposed scheme at a quality factor of 90. At a quality factor of 80, it can be observed that only the reference [32] is in closer proximity to the subject matter being discussed.…”

“…The findings indicate that the envisaged system exhibited satisfactory performance even in the presence of a noise attack. In addition, a comparative analysis was performed to evaluate the results of the proposed methodology in relation to other established approaches, specifically [28,[30][31][32], with respect to varying noise intensity levels of 0.001, 0.005, 0.010, and 0.020 (as presented in Table 7). The findings indicate that the outcomes of [28,30] bear a resemblance to the proposed scheme at intensity levels of 0.001 and 0.020.…”

“…The findings indicate that the outcomes of [28,30] bear a resemblance to the proposed scheme at intensity levels of 0.001 and 0.020. At an intensity level of 0.010, it is apparent that [30][31][32] exhibit superior performance. However, the performance of intensity level 0.005 surpasses that of [28,[30][31][32].…”

“…Moreover, the transform domain is often used to improve the imperceptibility of a watermarking scheme. There are several reports available in the literature, such as [17,18,[20][21][22][23][24][25][26][27][28][29][30][31][32].…”