A secure image authentication technique based on sparse approximation and quantum mechanism

The security and protection of digital content transmitted over a network are critical concerns due to with which various types of data can be transformed into text, images, audio, and video forms. This vulnerability makes them susceptible to unauthorized modifications by hackers. To address this issue, several techniques been developed, and one such approach is image encryption and watermarking. Watermarking offers for data authentication, copyright protection, and document ownership problems. This paper introduces algorithm based on Sparse Approximation (SA), Quantum Encryption (QE), and a measurement matrix to watermark encryption, as well as its secure transmission by embedding it in a host image. In this, the watermark image is divided into four sub -images, and then sparsification is performed transform domain. To further enhance security, the sparse data is transformed in the Discrete Transformation (DWT) domain, and a sparse coefficient exchange procedure is applied. Next, we generate measurement matrix, and the row and column vector of this matrix are filled by sequences which are generated by a quantum logistic map, and then perform encryption as well as data scrambled process. During encryption, updated pixel location is calculated based on a sparse sub -band coefficient exchange procedure. Based procedure, we exchange the sparse coefficient between the sub -images. Finally, we generate an encrypted watermark through a series of inverse sparsification, DWT, and sampling. These steps collectively fortify algorithms against various attacks, making them robust. The encrypted watermark information is used for authentication purposes and is embedded into the host using DWT and Singular Value Decomposition. The results are presented in various tabular and graphical forms, showcasing the effectiveness of the proposed method. The experimental results show that the techniques resist several attacks such as enhancement attacks, noise impact attacks, and geometrical A comparative analysis is also provided, comparing the results with existing approaches.