With the rapid development of digital multimedia technology, images, as an important carrier of information dissemination, have been widely applied in fields such as healthcare, security, commerce, and social networking. However, images are highly susceptible to tampering, duplication, and illegal use during transmission and storage, posing severe challenges to their authenticity and integrity. Traditional image authentication techniques exhibit significant deficiencies in terms of security, robustness, and invisibility, making them difficult to meet the increasing security demands. This paper proposes a novel image authentication method that integrates Sparse Approximation (SA) and Quantum Encryption (QE), aiming to enhance the security and anti-attack capabilities of digital images. The method first performs subsampling and sparsification on the watermark image, extracts multi-scale features of the image using Discrete Wavelet Transform (DWT), and generates a highly random measurement matrix through quantum logic mapping to achieve encryption and exchange of sparse coefficients. Subsequently, Singular Value Decomposition (SVD) is employed to embed the encrypted watermark information into the low-frequency components of the host image, ensuring the invisibility and robustness of the watermark. Experimental results demonstrate that the proposed method exhibits excellent performance in resisting noise, geometric transformations, and enhancement attacks. When the correct key is used, the watermark can be accurately recovered, while the use of an incorrect key results in complete distortion of the watermark, effectively preventing illegal extraction. The research presented in this paper provides an efficient and secure technical path for digital image copyright protection and content authentication.
Gan et al. (Fri,) studied this question.