Manuscript received June 14, 2023; revised July 6, 2023; accepted September 7, 2023.

Abstract—In the digital age, protecting the ownership and data veracity of digital documents is a major challenge. To address the issues concerning copyright protection and data verification of digital media, digital watermarking has emerged as a solution. In this paper, we aspire to make a modest contribution to this emerging and exciting field by presenting our proposed adaptive hybrid image watermarking approach that combines Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). Our method involves applying DWT to both the host image and watermark, followed by singular decomposition using SVD on the Low-Low (LL) component of both images. Now modify the singular values of the host image by the singular values of the watermark, and then inverse SVD is applied, followed by inverse DWT, to obtain the watermarked image. After that, the reverse process is applied to obtain the watermark image. Finally, we evaluate our approach’s performance by measuring the Peak Signal-to-Noise Ratio (PSNR) between the original and watermarked image as well as the Normalized Cross-Correlation (NCC) between the original and extracted watermark. Simulation results indicate that the proposed method is rich in terms of robustness, imperceptibility and capacity than the previously presented schemes.

Keywords—digital image watermarking, discrete wavelet transform, singular value decomposition, particle swarm optimization, Normalized Cross-Correlation (NCC) and Peak Signal-to-Noise Ratio (PSNR)

Cite: Sachin Gaur, Navneet Tripathi, and Jyoti Pandey, "A Hybrid DWT-SVD Based Adaptive Image Watermarking Scheme," Journal of Image and Graphics, Vol. 11, No. 4, pp. 414-427, December 2023.

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.