A significant data protection technique for a number of problems, the most prominent being identity authentication and copyright protection, is digital image watermarking. The rapid digital transformation of the world has given rise to a variety of vision modification techniques, which have significant consequences for picture data security. As a result, maintaining the validity and integrity of digital images is crucial, which is why researchers are focusing on creating effective watermarking techniques. This study proposes an optimized robust watermarking technique based on lifting wavelet transform (LWT) with singular value decomposition (SVD) using the particle swarm optimization (PSO) algorithm for achieving multiple scaling factors (MSF). To increase security and durability, cover images are exposed to numerous attacks. The evaluation criteria, which encompass normalized cross-correlation (NCC) and peak signal-to-noise ratio (PSNR), were used to compare our outcomes with those of leading watermarking methods. The comparison reveals that our proposed strategy surpasses existing methods in terms of both robustness and imperceptibility. The results suggest that this technique is suitable for tamper detection in various domains, including cryptography, medical imaging and multimedia transmission.
Keywords
Watermarking, Singular Value Decomposition, Lifting Wavelet Transform, Peak Signal-To-Noise Ratio and Particle Swarm Optimization.
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Supraja G
Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, Tamil Nadu, India.
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Cite this article
Praveenkumar Babu, Supraja G, Gopi Kasinathan, Kavitha Devi K, and Yogapriya J, “PSO-Optimized Watermarking Using Lifting Wavelet Transform and SVD for Enhanced Image Security”, Journal of Machine and Computing. doi: 10.53759/7669/jmc202505010.
