SNENet: An adaptive stego noise extraction network using parallel dilated convolution for JPEG image steganalysis
Abstract The steganalysis for JPEG image is an important research topic, as the enormous popularity of JPEG image on Internet. However, the stego noise feature extraction process of the existing deep learning‐based steganalytic methods are not adaptive enough to the content of the image, which may l...
Main Authors: | Wentong Fan, Zhenyu Li, Hao Li, Yi Zhang, Xiangyang Luo |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2023-08-01
|
Series: | IET Image Processing |
Subjects: | |
Online Access: | https://doi.org/10.1049/ipr2.12835 |
Similar Items
-
Stego key recovery method for F5 steganography with matrix encoding
by: Jiufen Liu, et al.
Published: (2020-09-01) -
Improved PHARM for JPEG Steganalysis: Making PHARM More Efficient and Effective
by: Chao Xia, et al.
Published: (2019-01-01) -
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
by: Inas Ali Abdulmunem, et al.
Published: (2021-12-01) -
Image Steganalysis with Binary Similarity Measures
by: Kharrazi Mehdi, et al.
Published: (2005-01-01) -
Color image steganalysis based on quaternion discrete cosine transform
by: Meng Xu, et al.
Published: (2023-05-01)