Name
Abstract | ||
|---|---|---|
Based on the feature analysis of image content, this paper proposes a novel steganalytic method for grayscale images in spatial domain. In this work, we firstly investigates directional lifting wavelet transform (DLWT) as a sparse representation in compressive sensing (CS) domain. Then a block CS (BCS) measurement matrix is designed by using the generalized Gaussian distribution (GGD) model, in which the measurement matrix can be used to sense the DLWT coefficients of images to reflect the feature residual introduced by steganography. Extensive experiments are showed that proposed scheme CS-based is feasible and universal for detecting stegography in spatial domain. |
Year | Venue | Field |
|---|---|---|
2017 | iThings/GreenCom/CPSCom/SmartData | Steganography,Pattern recognition,Computer science,Sparse approximation,Feature extraction,Artificial intelligence,Steganalysis,Grayscale,Compressed sensing,Sparse matrix,Wavelet transform |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huimin Zhao | 1 | 206 | 23.43 |
| Jingchang Ren | 2 | 0 | 0.34 |
| Zhenzhen Pei | 3 | 0 | 0.68 |
| Zhengye Cai | 4 | 0 | 0.68 |
| Qingyun Dai | 5 | 148 | 23.91 |
| Wenguo Wei | 6 | 0 | 1.01 |