Blind Audio Watermarking Based on Parametric Slant-Hadamard Transform and Hessenberg Decomposition

• Main Authors: Pranab Kumar Dhar, Azizul Hakim Chowdhury, Takeshi Koshiba
• Format: Article
• Language: English
• Published: MDPI AG 2020-02-01
• Series: Symmetry
• Subjects: audio watermarking; copyright protection; parametric slant-hadamard transform; hessenberg decomposition; euclidean normalization
• Online Access: https://www.mdpi.com/2073-8994/12/3/333

Digital watermarking has been widely utilized for ownership protection of multimedia contents. This paper introduces a blind symmetric audio watermarking algorithm based on parametric Slant-Hadamard transform (PSHT) and Hessenberg decomposition (HD). In our proposed algorithm, at first watermark image is preprocessed to enhance the security. Then, host signal is divided into non-overlapping frames and the samples of each frame are reshaped into a square matrix. Next, PSHT is performed on each square matrix individually and a part of this transformed matrix of size <i>m</i>&#215;<i>m</i><i> </i>is selected and HD is applied to it. Euclidean normalization is calculated from the 1st column of the Hessenberg matrix, which is further used for embedding and extracting the watermark. Simulation results ensure the imperceptibility of the proposed method for watermarked audios. Moreover, it is demonstrated that the proposed algorithm is highly robust against numerous attacks. Furthermore, comparative analysis substantiates its superiority among other state-of-the-art methods.