Hybrid fragile image watermarking for tamper detection, localization and dual self-recovery

This paper presents a novel image watermarking framework that effectively addresses the issue of random block mapping. This phenomenon compromises tampered regions and their corresponding recovery blocks, resulting in irretrievable image data. To mitigate the random block mapping issue, a crisscross block mapping strategy (CrCsBMS) is proposed to enhance the robustness of block mapping by ensuring non-randomised reference allocation. The authentication bit generation leverages Gram-Schmidt Orthonormalization (GSO), extracting pivotal image characteristics, such as mean intensity, variance, and edge strength, thereby fortifying the integrity verification mechanism. The hybrid embedding strategy integrates discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD) to maintain an optimal balance between imperceptibility and embedding capacity, while distortion compensated quantization index modulation (DC-QIM) is employed for recovery bit encoding. A dual self-recovery mechanism incorporating bilinear interpolation-based inpainting and an 8-neighborhood method with a 255-color range scaling (255-CRS) is introduced, significantly augmenting recovery efficiency and ensuring precise restoration of tampered pixels. Experimental analysis demonstrates superior imperceptibility, robustness against image processing attacks, and reduced computational complexity compared to contemporary techniques. The proposed scheme achieves an average PSNR of 52.22 dB, an SSIM of 0.9983, and a payload capacity of 1 bit per pixel, surpassing existing self-recovery watermarking frameworks in both accuracy and resilience.