Optimized Video Watermarking With Entropy-Aware Block Selection and Modified Hénon-Map Encryption

Abstract

Video watermarking is a technique used to embed information into video content, ensuring privacy protection and preventing data misuse. However, watermarking schemes that rely on a single transform method are often vulnerable to noise and geometric distortions. To overcome these limitations, this study introduces a hybrid approach that combines singular value decomposition with discrete wavelet transform and redundant discrete wavelet transform for more effective watermark embedding. The proposed method optimizes the balance between imperceptibility and robustness by fine-tuning the scale factor through a custom fitness function using fruit fly optimization. The watermark is adaptively embedded based on the video's transform type, sub-band selection, attack types, and keyframes. Block selection within sub-bands is guided by entropy, edge entropy, and contrast. Watermark embedding and extraction are performed on selected blocks that meet these criteria. Experimental results evaluated using metrics such as normalized cross-correlation, image fidelity, and peak signal-to-noise ratio, demonstrate the superiority of our method over state-of-the-art methods.