Sinhal Rishi, Sharma Sachin, Ansari Irshad Ahmad, Bajaj Varun
Electronics and Communication Engineering, PDPM Indian Institute of Information Technology Design and Manufacturing, Jabalpur, MP 482005 India.
Research Division, Jagadish Chandra Bose Research Organisation, Gautam Budh Nagar, Uttar Pradesh 203207 India.
Multimed Tools Appl. 2022;81(10):14045-14063. doi: 10.1007/s11042-022-12082-0. Epub 2022 Feb 25.
Digital medical images contain important information regarding patient's health and very useful for diagnosis. Even a small change in medical images (especially in the region of interest (ROI)) can mislead the doctors/practitioners for deciding further treatment. Therefore, the protection of the images against intentional/unintentional tampering, forgery, filtering, compression and other common signal processing attacks are mandatory. This manuscript presents a multipurpose medical image watermarking scheme to offer copyright/ownership protection, tamper detection/localization (for ROI (region of interest) and different segments of RONI (region of non-interest)), and self-recovery of the ROI with 100% reversibility. Initially, the recovery information of the host image's ROI is compressed using LZW (Lempel-Ziv-Welch) algorithm. Afterwards, the robust watermark is embedded into the host image using a transform domain based embedding mechanism. Further, the 256-bit hash keys are generated using SHA-256 algorithm for the ROI and eight RONI regions (i.e. RONI-1 to RONI-8) of the robust watermarked image. The compressed recovery data and hash keys are combined and then embedded into the segmented RONI region of the robust watermarked image using an LSB replacement based fragile watermarking approach. Experimental results show high imperceptibility, high robustness, perfect tamper detection, significant tamper localization, and perfect recovery of the ROI (100% reversibility). The scheme doesn't need original host or watermark information for the extraction process due to the blind nature. The relative analysis demonstrates the superiority of the proposed scheme over existing schemes.
数字医学图像包含有关患者健康的重要信息，对诊断非常有用。即使医学图像中出现微小变化（尤其是在感兴趣区域（ROI）），也可能误导医生/从业者做出进一步治疗的决定。因此，必须保护图像免受有意/无意的篡改、伪造、滤波、压缩及其他常见信号处理攻击。本文提出了一种多用途医学图像水印方案，以提供版权/所有权保护、篡改检测/定位（针对ROI（感兴趣区域）和RONI（非感兴趣区域）的不同部分）以及ROI的完全可逆自恢复。首先，使用LZW（Lempel-Ziv-Welch）算法对宿主图像ROI的恢复信息进行压缩。之后，使用基于变换域的嵌入机制将鲁棒水印嵌入宿主图像。此外，针对鲁棒水印图像的ROI和八个RONI区域（即RONI-1至RONI-8），使用SHA-256算法生成256位哈希密钥。将压缩后的恢复数据和哈希密钥组合起来，然后使用基于最低有效位替换的脆弱水印方法嵌入到鲁棒水印图像的分割RONI区域中。实验结果表明，该方案具有高不可感知性、高鲁棒性、完美的篡改检测、显著的篡改定位以及ROI的完美恢复（100%可逆性）。由于具有盲性，该方案在提取过程中不需要原始宿主或水印信息。相对分析表明了该方案相对于现有方案的优越性。
