Optimized Hybrid DTCWT with Arnolds Cat Map Watermarking Scheme for Multi-Modal Digital Evidence
Amit A. Kale, Mahesh. S. Chanvan · 2024
Distinctive identifier or mark is embedded into an image through the technique of watermarking in order to prevent unauthorized usage or distribution. The degree to which these watermarks are resilient to different types of disruptions determines how reliable and effective they are. Nevertheless, nothing is known about how reliable these watermarks are in actual situations, especially when there are disruptions and malfeasance. So, an optimized hybrid algorithm is developed. Multimodal digital evidence, such as text, photos, audio, and video, is gathered and watermarked to provide evidence security. The provided digital evidence is divided into subspaces using the Discrete Wavelet Transform (DWT). After selecting these Low-Low subspaces, they are then divided into three levels using the Dual Tree Complex Wavelet Transform (DTCWT). Sooty Tern Optimization Algorithm (STOA) is used to optimally select the scaling function in the DTCWT algorithm. Arnold’s cat map is utilized to rearrange the pixels at random to render the image visually unintelligible. The performance metrics such as PSNR, SSIM and SNR of the proposed model are 67.4, 0.91and 0.92.