Semi-Fragile Watermarking Scheme for High-Resolution Color Images: Tamper Identification, Ownership Authentication, and Self-Recovery

The advancements in communication and information technologies have substantially enabled the extensive distribution and modification of high-resolution color images. Although this accessibility provides many advantages, it also presents risks related to security. Specifically, when image modification is conducted with malicious intent, exceeding typical artistic or enhancement objectives, it can cause significant moral or economic harm to the image owner. To address this security requirement, this study presents an innovative semi-fragile watermarking algorithm designed specifically for high-resolution color images. The proposed method utilizes Discrete Cosine Transform domain watermarking implemented via Quantization Index Modulation with Dither Modulation. It incorporates several elements, such as convolutional encoding, a denoising convolutional neural network, and a very deep super-resolution neural network. This comprehensive strategy aims to provide ownership verification using a logo watermark, in conjunction with tamper detection and content self-recovery mechanisms. The self-recovery criterion is determined using a thumbnail image, created by downscaling to standard definition and applying JPEG2000 lossy compression. The resultant multifunctional design enhances the overall security of the information. Experimental validation confirms the enhanced imperceptibility, robustness, and capacity of the proposed method. Its efficacy was additionally corroborated through comparative analyses using contemporary state-of-the-art algorithms.