Name
Abstract | ||
|---|---|---|
Watermarking performance enhancement has always been a difficult task since the performance metrics of watermarking systems, i.e., fidelity, robustness, and payload size, inherently conflict with each other. Nowadays, most watermarking schemes hide payloads according to predefined rules or empirical perceptual models. Therefore, the performance of digital watermarking schemes can be determined only passively. In this study, a genetic algorithm-based framework for watermarking performance enhancement is proposed. Watermarked results having better robustness, guaranteed fidelity, and fixed payload size can be obtained. Existing blind-detection watermarking schemes can be improved significantly by incorporating the proposed framework. In addition, the proposed framework has many desirable advantages such as asymmetric embedding/detection overhead, easy integration with existing data-hiding schemes, and direct control over fidelity and robustness. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.ins.2008.10.035 | Inf. Sci. |
Keywords | Field | DocType |
digital watermarking fidelity robustness genetic algorithms gas,blind-detection watermarking scheme,proposed framework,guaranteed fidelity,watermarking scheme,better robustness,watermarking system,fidelity-guaranteed robustness enhancement,digital watermarking scheme,watermarking performance enhancement,performance metrics,genetic algorithm-based framework,genetic algorithm,digital watermark,data hiding,digital watermarking,robustness | Digital watermarking,Fidelity,Theoretical computer science,Robustness (computer science),Artificial intelligence,Computer engineering,Genetic algorithm,Payload,Embedding,Performance enhancement,Direct control,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
179 | 6 | 0020-0255 |
Citations | PageRank | References |
19 | 1.24 | 16 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chun-Hsiang Huang | 1 | 138 | 12.05 |
| Ja-ling Wu | 2 | 1569 | 168.11 |