A new video watermarking using redundant discrete wavelet in singular value decomposition domain with multi‐objective optimization

Abstract

Day by day, the transmission or sharing of digital information online is increasing due to the fact that Internet usage has become somewhat of an addiction for the majority of people. This results in larger copyright violation problems. Nowadays, most of the data or information is being transmitted in the form of digital images or videos, which are rather simple for the violators of copyright to forge or fake and then share for profit. Thus, digital watermarking came into existence as a possible solution to address these violations of copyright. This article proposes a new blind video watermarking (BVW) using redundant discrete wavelet transform (RDWT) in singular value decomposition (SVD) domain, which utilizes the advantages of both RDWT and SVD to embed and extract the watermark information into the cover video without degrading the quality of the watermark. In addition, an efficient meta‐heuristic optimization with multi‐objective optimization (MOO) is employed to further optimize the proposed RDWT‐SVD approach. Further, various attacks were applied to the watermarked frame to disclose the robustness of proposed BVW using RDWT‐SVD with MOO approach. Extensive simulations on several test videos with comparison to the conventional BVW methodologies exhibit the transcendency of the proposed BVW using RDWT‐SVD with MOO approach in terms of watermarking quality evaluation metrics such as peak signal‐to‐noise ratio (PSNR), structural similarity index, normalized correlation, and even that of root mean square error as well.

Blind video watermarking scheme for medical video authentication

“…In the third experiment, the robustness of the proposed scheme was compared with other watermarking schemes established by [9, 18, 49, 59, +[ 60 ]] for most joint attacks. The obtained NC values of our scheme significantly surpass the compared schemes, as displayed in ( Table 6 ).…”

Imperceptible Improvement using Edge Area Selection for Robust Video Watermarking Using Tchebichef - Singular Value Decomposition

“…SVD is a numerical analysis method that is widely used for various image processing applications [18], which can also be implemented in video watermarking [1,19,20]. This method performs a numerical analysis by decomposing the original matrix (𝑍) with size (𝑀 × 𝑁) of rank 𝑟 (the rank of a complex matrix Z that represents a specific value of a non-zero singular value) into three matrices of the same size.…”