Image Robust Watermarking Method Based on DWT-SVD Transform and Chaotic Map

Abstract

The existing watermarking algorithms make it difficult to balance the invisibility and robustness of the watermark. This paper proposes a robust image watermarking method based on discrete wavelet transform (DWT), singular value decomposition (SVD), and chaotic maps. This method is a semiblind watermarking method. First, a chaotic logistic-tent map is introduced, employing an extensive chaotic parameter domain. This map is amalgamated with Arnold’s transformation to encrypt the watermark image, thereby bolstering the security of the watermark information. Subsequently, the frequency domain is obtained by applying DWT to the carrier image. Embedding watermarks in the frequency domain ensures the invisibility of the watermark, with a preference for a high-frequency subband after the DWT of the carrier image for enhanced watermark robustness. SVD is then applied to both the high-frequency subband of the carrier image after DWT and the encrypted watermark image. The final step involves embedding the singular values of the encrypted watermark image into the carrier image’s singular values, thereby completing the watermark information embedding process. In simulation experiments, an invisibility test was conducted on various carrier images, yielding peak signal-to-noise ratio (PSNR) values consistently exceeding 43, and structural similarity (SSIM) close to 1. Robustness testing against various types of attacks resulted in normalized correlation (NC) values consistently surpassing 0.9, with bit error rate (BER) values approaching 0. In conclusion, the proposed algorithm satisfies imperceptibility requirements while demonstrating formidable robustness.