Name
Abstract | ||
|---|---|---|
This paper presents a novel adjustable audio watermarking method with high auditory quality by exploiting the discrete wavelet packet transform (DWPT), psychoacoustic modeling and distortion compensated-dither modulation (DC-DM) quantization. While the DWPT is used to divide the audio frames into several frequency sub-bands, the psychoacoustic model is intergraded to determine the appropriate sub-bands for watermarking and to control the number of embedded bits in each one. Then, the DC-DM technique is used to embed the watermark bits into the appropriate DWPT coefficients. The synchronization code technique is adopted in the proposed method to withstand desynchronization attacks. In order to achieve an adjustable watermarking scheme, two regulator parameters are provided to manage the capacity-robustness trade-off. The performance of the watermarking scheme is evaluated by examining different host audio signals under various watermarking attacks. The results show excellent imperceptibility of watermarked signals with an average ODG of − 0.3. In addition, the proposed scheme provides strong robustness against the attacks with low capacity. However, high capacity (about 2500 bps) can be achieved while maintaining a reasonable robustness. A comparison with some state-of-the-art audio watermarking schemes reveals that the proposed method provides competitive results. |
Year | DOI | Venue |
|---|---|---|
2018 | https://doi.org/10.1007/s11042-017-4813-8 | Multimedia Tools Appl. |
Keywords | Field | DocType |
Digital audio watermarking,Discrete wavelet packet transform,Quantization index modulation,Distortion compensated-dither modulation,Psychoacoustic modeling | Audio signal,Digital watermarking,Synchronization,Pattern recognition,Computer science,Algorithm,Watermark,Robustness (computer science),Modulation,Artificial intelligence,Quantization (signal processing),Distortion | Journal |
Volume | Issue | ISSN |
77 | 10 | 1380-7501 |
Citations | PageRank | References |
1 | 0.36 | 31 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mustapha Hemis | 1 | 4 | 0.76 |
| bachir boudraa | 2 | 12 | 4.79 |
| David Megías | 3 | 205 | 24.13 |
| Thouraya Merazi-Meksen | 4 | 1 | 0.36 |