Improving Video Watermarking through Galois Field GF(2⁴) Multiplication Tables with Diverse Irreducible Polynomials and Adaptive Techniques

Video watermarking plays a crucial role in protecting intellectual property rights and ensuring content authenticity. This study delves into the integration of Galois Field (GF) multiplication tables, especially GF(24), and their interaction with distinct irreducible polynomials. The primary aim is to enhance watermarking techniques for achieving imperceptibility, robustness, and efficient execution time. The research employs scene selection and adaptive thresholding techniques to streamline the watermarking process. Scene selection is used strategically to embed watermarks in the most vital frames of the video, while adaptive thresholding methods ensure that the watermarking process adheres to imperceptibility criteria, maintaining the video’s visual quality. Concurrently, careful consideration is given to execution time, crucial in real-world scenarios, to balance efficiency and efficacy. The Peak Signal-to-Noise Ratio (PSNR) serves as a pivotal metric to gauge the watermark’s imperceptibility and video quality. The study explores various irreducible polynomials, navigating the trade-offs between computational efficiency and watermark imperceptibility. In parallel, the study pays careful attention to the execution time, a paramount consideration in real-world scenarios, to strike a balance between efficiency and efficacy. This comprehensive analysis provides valuable insights into the interplay of GF multiplication tables, diverse irreducible polynomials, scene selection, adaptive thresholding, imperceptibility, and execution time. The evaluation of the proposed algorithm’s robustness was conducted using PSNR and NC metrics, and it was subjected to assessment under the impact of five distinct attack scenarios. These findings contribute to the development of watermarking strategies that balance imperceptibility, robustness, and processing efficiency, enhancing the field’s practicality and effectiveness.