Adaptive tamper detection watermarking scheme for medical images in transform domain

A novel robust tamper detection medical watermarking scheme is proposed in the transform domain for authentication and detecting tamper pixels of medical images. In this scheme, 2-level Discrete Wavelet Transform is applied to a significant image to produce four sub-bands (SB) (C-LL,C-LH,C-HL,C-HH). Coefficients of LL sub-bands are considered in embedding the watermark. The SB is partitioned into blocks to overcome image processing attacks. LSB is set to zero for each block and then Schur decomposition is applied in generating Authenticated Block Bits (ABB). In developing confusion to the intruders, the watermark is scrambled using Quantum Hilbert Image Scrambling. Watermarking helps in authentication and tamper detection of the significant image after tampering. The scheme is tested with image processing attacks for robustness. Peak signal to noise ratio (PSNR) and Normalized Cross-Correlation (NCC) metrics are utilized as metrics in evaluating the proposed scheme with PSNR greater than 30dB and NCC values nearer to 1 without attacks and even with attacks, NCC values are greater than 0.95, which shows the robustness of the proposed scheme.