Name
Title | ||
|---|---|---|
A difference matching technique for data embedment based on absolute moment block truncation coding |
Abstract | ||
|---|---|---|
In this paper, an optimized data embedding method based on Huang et al.’s work for absolute moment block truncation coding (AMBTC) is proposed. Huang et al.’s work successfully exploits the difference of quantization levels (QLs) for data embedment and has an excellent embedding performance. However, the modified QLs are not adjusted to minimize the distortion. In some rare cases, they might exceed the grayscale range. Moreover, the order of QLs in smooth blocks is not utilized for data embedment, losing the chance to embed one additional bit without deteriorating the image block. We propose a method to give analytical solutions to adjust QLs such that the distortions in both smooth and complex blocks are minimized. A subtle mechanism is also provided to ensure that no QLs will overflow or underflow. Moreover, the order of QLs is utilized in data embedment to further increase the payload without sacrificing the image quality. The experimental results reveal that the proposed method offers a better image quality over Huang et al.’s and other state-of-the-art works while providing a comparable or larger payload. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s11042-018-6983-4 | Multimedia Tools and Applications |
Keywords | Field | DocType |
AMBTC, Data embedding, Difference matching | Computer vision,Arithmetic underflow,Block Truncation Coding,Embedding,Computer science,Embedment,Image quality,Artificial intelligence,Quantization (signal processing),Distortion,Grayscale | Journal |
Volume | Issue | ISSN |
78.0 | 10 | 1573-7721 |
Citations | PageRank | References |
0 | 0.34 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wien Hong | 1 | 618 | 30.63 |
| Yizhen Li | 2 | 0 | 0.34 |
| Weng ShaoWei | 3 | 78 | 10.33 |