Year: 2020
Type: conference-paper
Abstract: Graph-based Transform (GT) has been recently leveraged successfully in signal processing domain, specifically for compression purposes. In this paper, we employ the GBT, as well as the Singular Value Decomposition (SVD) with the goal to improve the robustness of audio watermarking against different attacks on the audio signals, such as noise and compression. Experimental results on the NOIZEUS speech database and MIR-1k music database clearly certify that the proposed GBT-SVD-based method is robust against the attacks. Moreover, the results exhibit a good quality after the embedding based on PSNR, PESQ and STOI measures. In addition, the payload for the proposed method is 800 and 1600 for speech and music signals, respectively which is higher than some robust watermarking methods such as DWT-SVD and DWT-DCT.
Authors: Majid Farzaneh, Rahil Mahdian Toroghi
Institution: Iran Broadcasting University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3011665477