Name
Abstract | ||
|---|---|---|
Recently, a number of high-fidelity reversible data hiding algorithms have been developed based on prediction-error expansion (PEE) and pixel sorting. In PEE, prediction is made using either a full-enclosed or a half-enclosed predictor. While in PEE with pixel sorting, the local complexity (LC), which is usually assumed to be proportional to the magnitude of prediction-error (PE), is exploited to reduce the embedding distortion. However, this assumption may not always hold in all conditions. In this letter, a directional enclosed predictor is proposed to detect the locations where LC is not proportional to PE. And, a directionally enclosed prediction and expansion (DEPE) scheme is then developed for efficient reversible data hiding. With DEPE, data embedding is restricted to pixels where LC correlates to PE with a proportional relationship. Experimental results show that, compared to the full-enclosed or half-enclosed prediction schemes, DEPE significantly improves the image fidelity while providing a considerable payload. |
Year | Venue | Field |
|---|---|---|
2017 | IEEE Signal Process. Lett. | High fidelity,Histogram,Embedding,Pattern recognition,Information hiding,Algorithm,Sorting,Artificial intelligence,Pixel,Distortion,Mathematics,Payload |
DocType | Volume | Issue |
Journal | 24 | 5 |
Citations | PageRank | References |
8 | 0.47 | 15 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haishan Chen | 1 | 19 | 2.00 |
| Jiangqun Ni | 2 | 453 | 34.31 |
| Wien Hong | 3 | 618 | 30.63 |
| Tungshou Chen | 4 | 1082 | 89.79 |