A Resilient Video Wavering Approach Using Dualistic-Tree Complicated Wavelength Transmute and Solo Virtue Disintegration for Enhanced Security and Resilience

Abstract

Wavering can be used in digital multimedia for securing content to prevent misuse and ensure its authenticity. In this paper, we are presenting a novel video wavering scheme which integrates Dualistic-Tree Complicated Wavelength Transmute (DTCWT) with Solo Virtue Disintegration (SVD), thereby enhancing robustness of waver embedding along with better extraction fidelity. The DTCWT provides the system with high directional sensitivity, allowing it to capture video content details. SVD helps stabilize the embedding in the waver, thus providing the system with a significant amount of resistance to many attacks and distortions. We compare our proposed DTCWT-SVD model against traditional frameworks, such as Distinct Wavelength Transmute-SVD (DWT-SVD), Distinct Cosinus Transmute-SVD (DCT-SVD), and Redundant Distinct Wavelength Transmute-SVD (RDWT-SVD) to measure resilientness, imperceptibility, quality of extracted waver, capacity, computational efficiency, and security. Experimental results show that the suggested DTCWT-SVD framework outperforms all other frameworks in terms of noise robustness, compression, and geometric distortions. For instance, the suggested model achieves a high NC score, which indicates that waver quality extracted from its model is constantly superior compared to its competitors' NC values are more than 0.9, signifying excellent fidelity. Also, the DTCWT-SVD model exhibits low complexity compared to RDWT-SVD, and therefore, the model can be used for real-time applications practically. A detailed security analysis confirms that DTCWT-SVD offers solid cryptographic strength to safeguard the waver against any type of unauthorized extraction. This proposed model retains a PSNR value at a satisfactory level for imperceptibility, meaning that the original video quality is not visibly affected by the waver. In addition, its ability to support larger wavers does not degrade the quality proves it to be a well-suited candidate for applications requiring high standards of security. These results highlight that the proposed DTCWT-SVD framework is viable in yielding robust and efficient shakiness and open up several future developments on video content protection. Some of these directions would include improving its adaptability towards real-time video streaming scenarios, hybrid model approaches coupled with machine learning to resist more attacks, and improved efficiency on resource constraints.